Measurement Of Multiphase Flow Water Fraction And Water-cut

NASA Astrophysics Data System (ADS)

Xie, Cheng-gang

2007-06-01

This paper describes a microwave transmission multiphase flow water-cut meter that measures the amplitude attenuation and phase shift across a pipe diameter at multiple frequencies using cavity-backed antennas. The multiphase flow mixture permittivity and conductivity are derived from a unified microwave transmission model for both water- and oil-continuous flows over a wide water-conductivity range; this is far beyond the capability of microwave-resonance-based sensors currently on the market. The water fraction and water cut are derived from a three-component gas-oil-water mixing model using the mixture permittivity or the mixture conductivity and an independently measured mixture density. Water salinity variations caused, for example, by changing formation water or formation/injection water breakthrough can be detected and corrected using an online water-conductivity tracking technique based on the interpretation of the mixture permittivity and conductivity, simultaneously measured by a single-modality microwave sensor.

A dual-trace model for visual sensory memory.

PubMed

Cappiello, Marcus; Zhang, Weiwei

2016-11-01

Visual sensory memory refers to a transient memory lingering briefly after the stimulus offset. Although previous literature suggests that visual sensory memory is supported by a fine-grained trace for continuous representation and a coarse-grained trace of categorical information, simultaneous separation and assessment of these traces can be difficult without a quantitative model. The present study used a continuous estimation procedure to test a novel mathematical model of the dual-trace hypothesis of visual sensory memory according to which visual sensory memory could be modeled as a mixture of 2 von Mises (2VM) distributions differing in standard deviation. When visual sensory memory and working memory (WM) for colors were distinguished using different experimental manipulations in the first 3 experiments, the 2VM model outperformed Zhang and Luck (2008) standard mixture model (SM) representing a mixture of a single memory trace and random guesses, even though SM outperformed 2VM for WM. Experiment 4 generalized 2VM's advantages of fitting visual sensory memory data over SM from color to orientation. Furthermore, a single trace model and 4 other alternative models were ruled out, suggesting the necessity and sufficiency of dual traces for visual sensory memory. Together these results support the dual-trace model of visual sensory memory and provide a preliminary inquiry into the nature of information loss from visual sensory memory to WM. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Continuous spin detonation of poorly detonable fuel-air mixtures in annular combustors

NASA Astrophysics Data System (ADS)

Bykovskii, F. A.; Zhdan, S. A.

2017-09-01

This paper reports on the results of experimental investigations of continuous spin detonation of three fuel-air mixtures (syngas-air, CH4/H2-air, and kerosene/H2-air in a flow-type annular cylindrical combustor 503 mm in diameter. The limits of existence of continuous detonation in terms of the specific flow rates of the mixtures (minimum values) are determined. It is found that all gas mixtures, including the least detonable methane-air mixture, with addition of hydrogen can be burned in the continuous spin detonation regime.

A general mixture model and its application to coastal sandbar migration simulation

NASA Astrophysics Data System (ADS)

Liang, Lixin; Yu, Xiping

2017-04-01

A mixture model for general description of sediment laden flows is developed and then applied to coastal sandbar migration simulation. Firstly the mixture model is derived based on the Eulerian-Eulerian approach of the complete two-phase flow theory. The basic equations of the model include the mass and momentum conservation equations for the water-sediment mixture and the continuity equation for sediment concentration. The turbulent motion of the mixture is formulated for the fluid and the particles respectively. A modified k-ɛ model is used to describe the fluid turbulence while an algebraic model is adopted for the particles. A general formulation for the relative velocity between the two phases in sediment laden flows, which is derived by manipulating the momentum equations of the enhanced two-phase flow model, is incorporated into the mixture model. A finite difference method based on SMAC scheme is utilized for numerical solutions. The model is validated by suspended sediment motion in steady open channel flows, both in equilibrium and non-equilibrium state, and in oscillatory flows as well. The computed sediment concentrations, horizontal velocity and turbulence kinetic energy of the mixture are all shown to be in good agreement with experimental data. The mixture model is then applied to the study of sediment suspension and sandbar migration in surf zones under a vertical 2D framework. The VOF method for the description of water-air free surface and topography reaction model is coupled. The bed load transport rate and suspended load entrainment rate are all decided by the sea bed shear stress, which is obtained from the boundary layer resolved mixture model. The simulation results indicated that, under small amplitude regular waves, erosion occurred on the sandbar slope against the wave propagation direction, while deposition dominated on the slope towards wave propagation, indicating an onshore migration tendency. The computation results also shows that the suspended load will also make great contributions to the topography change in the surf zone, which is usually neglected in some previous researches.

A corrected formulation for marginal inference derived from two-part mixed models for longitudinal semi-continuous data

PubMed Central

Su, Li; Farewell, Vernon T

2013-01-01

For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that provided convenient estimation of marginal effects for the logistic component of the two-part model but the specification of marginal effects for the continuous part of the model presented in that paper was based on an incorrect formulation. We present a corrected formulation and additionally explore the use of the two-part model for inferences on the overall marginal mean, which may be of more practical relevance in our application and more generally. PMID:24201470

A numerical model for boiling heat transfer coefficient of zeotropic mixtures

NASA Astrophysics Data System (ADS)

Barraza Vicencio, Rodrigo; Caviedes Aedo, Eduardo

2017-12-01

Zeotropic mixtures never have the same liquid and vapor composition in the liquid-vapor equilibrium. Also, the bubble and the dew point are separated; this gap is called glide temperature (Tglide). Those characteristics have made these mixtures suitable for cryogenics Joule-Thomson (JT) refrigeration cycles. Zeotropic mixtures as working fluid in JT cycles improve their performance in an order of magnitude. Optimization of JT cycles have earned substantial importance for cryogenics applications (e.g, gas liquefaction, cryosurgery probes, cooling of infrared sensors, cryopreservation, and biomedical samples). Heat exchangers design on those cycles is a critical point; consequently, heat transfer coefficient and pressure drop of two-phase zeotropic mixtures are relevant. In this work, it will be applied a methodology in order to calculate the local convective heat transfer coefficients based on the law of the wall approach for turbulent flows. The flow and heat transfer characteristics of zeotropic mixtures in a heated horizontal tube are investigated numerically. The temperature profile and heat transfer coefficient for zeotropic mixtures of different bulk compositions are analysed. The numerical model has been developed and locally applied in a fully developed, constant temperature wall, and two-phase annular flow in a duct. Numerical results have been obtained using this model taking into account continuity, momentum, and energy equations. Local heat transfer coefficient results are compared with available experimental data published by Barraza et al. (2016), and they have shown good agreement.

A pattern-mixture model approach for handling missing continuous outcome data in longitudinal cluster randomized trials.

PubMed

Fiero, Mallorie H; Hsu, Chiu-Hsieh; Bell, Melanie L

2017-11-20

We extend the pattern-mixture approach to handle missing continuous outcome data in longitudinal cluster randomized trials, which randomize groups of individuals to treatment arms, rather than the individuals themselves. Individuals who drop out at the same time point are grouped into the same dropout pattern. We approach extrapolation of the pattern-mixture model by applying multilevel multiple imputation, which imputes missing values while appropriately accounting for the hierarchical data structure found in cluster randomized trials. To assess parameters of interest under various missing data assumptions, imputed values are multiplied by a sensitivity parameter, k, which increases or decreases imputed values. Using simulated data, we show that estimates of parameters of interest can vary widely under differing missing data assumptions. We conduct a sensitivity analysis using real data from a cluster randomized trial by increasing k until the treatment effect inference changes. By performing a sensitivity analysis for missing data, researchers can assess whether certain missing data assumptions are reasonable for their cluster randomized trial. Copyright © 2017 John Wiley & Sons, Ltd.

A corrected formulation for marginal inference derived from two-part mixed models for longitudinal semi-continuous data.

PubMed

Tom, Brian Dm; Su, Li; Farewell, Vernon T

2016-10-01

For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that provided convenient estimation of marginal effects for the logistic component of the two-part model but the specification of marginal effects for the continuous part of the model presented in that paper was based on an incorrect formulation. We present a corrected formulation and additionally explore the use of the two-part model for inferences on the overall marginal mean, which may be of more practical relevance in our application and more generally. © The Author(s) 2013.

Modeling water partition in composite gels of BSA with gelatin following high pressure treatment.

PubMed

Semasaka, Carine; Mhaske, Pranita; Buckow, Roman; Kasapis, Stefan

2018-11-01

Changes in the structural properties of hydrogels made with gelatin and bovine serum albumin mixtures were recorded following exposure to high pressure at 300 MPa for 15 min at 10 and 80 °C. Dynamic oscillation, SEM, FTIR and blending law modelling were utilised to rationalise results. Pressurization at the low temperature end yielded continuous gelatin networks supporting discontinuous BSA inclusions, whereas an inverted dispersion was formed at the high temperature end with the continuous BSA network suspending the discontinuous gelatin inclusions. Lewis and Nielsen equations followed the mechanical properties of the composites thus arguing that solvent partition between the two phases was always in favour of the polymer forming the continuous network. As far as we are aware, this is the first attempt to elucidate the solvent partition in pressurised hydrogel composites using blending law theory. Outcomes were contrasted with earlier work where binary mixtures were subjected only to thermal treatment. Copyright © 2018. Published by Elsevier Ltd.

Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures

NASA Astrophysics Data System (ADS)

Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany

2016-07-01

Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.

Modeling Working Memory Tasks on the Item Level

ERIC Educational Resources Information Center

Luo, Dasen; Chen, Guopeng; Zen, Fanlin; Murray, Bronwyn

2010-01-01

Item responses to Digit Span and Letter-Number Sequencing were analyzed to develop a better-refined model of the two working memory tasks using the finite mixture (FM) modeling method. Models with ordinal latent traits were found to better account for the independent sources of the variability in the tasks than those with continuous traits, and…

Development of a new continuous process for mixing of complex non-Newtonian fluids

NASA Astrophysics Data System (ADS)

Migliozzi, Simona; Mazzei, Luca; Sochon, Bob; Angeli, Panagiota; Thames Multiphase Team; Coral Project Collaboration

2017-11-01

Design of new continuous mixing operations poses many challenges, especially when dealing with highly viscous non-Newtonian fluids. Knowledge of complex rheological behaviour of the working mixture is crucial for development of an efficient process. In this work, we investigate the mixing performance of two different static mixers and the effects of the mixture rheology on the manufacturing of novel non-aqueous-based oral care products using experimental and computational fluid dynamic methods. The two liquid phases employed, i.e. a carbomer suspension in polyethylene glycol and glycerol, start to form a gel when they mix. We studied the structure evolution of the liquid mixture using time-resolved rheometry and we obtained viscosity rheograms at different phase ratios from pressure drop measurements in a customized mini-channel. The numerical results and rheological model were validated with experimental measurements carried out in a specifically designed setup. EPSRS-CORAL.

A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores

PubMed Central

Neelon, Brian; Gelfand, Alan E.; Miranda, Marie Lynn

2013-01-01

Summary Researchers in the health and social sciences often wish to examine joint spatial patterns for two or more related outcomes. Examples include infant birth weight and gestational length, psychosocial and behavioral indices, and educational test scores from different cognitive domains. We propose a multivariate spatial mixture model for the joint analysis of continuous individual-level outcomes that are referenced to areal units. The responses are modeled as a finite mixture of multivariate normals, which accommodates a wide range of marginal response distributions and allows investigators to examine covariate effects within subpopulations of interest. The model has a hierarchical structure built at the individual level (i.e., individuals are nested within areal units), and thus incorporates both individual- and areal-level predictors as well as spatial random effects for each mixture component. Conditional autoregressive (CAR) priors on the random effects provide spatial smoothing and allow the shape of the multivariate distribution to vary flexibly across geographic regions. We adopt a Bayesian modeling approach and develop an efficient Markov chain Monte Carlo model fitting algorithm that relies primarily on closed-form full conditionals. We use the model to explore geographic patterns in end-of-grade math and reading test scores among school-age children in North Carolina. PMID:26401059

A new approach for handling longitudinal count data with zero-inflation and overdispersion: poisson geometric process model.

PubMed

Wan, Wai-Yin; Chan, Jennifer S K

2009-08-01

For time series of count data, correlated measurements, clustering as well as excessive zeros occur simultaneously in biomedical applications. Ignoring such effects might contribute to misleading treatment outcomes. A generalized mixture Poisson geometric process (GMPGP) model and a zero-altered mixture Poisson geometric process (ZMPGP) model are developed from the geometric process model, which was originally developed for modelling positive continuous data and was extended to handle count data. These models are motivated by evaluating the trend development of new tumour counts for bladder cancer patients as well as by identifying useful covariates which affect the count level. The models are implemented using Bayesian method with Markov chain Monte Carlo (MCMC) algorithms and are assessed using deviance information criterion (DIC).

Adapting cultural mixture modeling for continuous measures of knowledge and memory fluency.

PubMed

Tan, Yin-Yin Sarah; Mueller, Shane T

2016-09-01

Previous research (e.g., cultural consensus theory (Romney, Weller, & Batchelder, American Anthropologist, 88, 313-338, 1986); cultural mixture modeling (Mueller & Veinott, 2008)) has used overt response patterns (i.e., responses to questionnaires and surveys) to identify whether a group shares a single coherent attitude or belief set. Yet many domains in social science have focused on implicit attitudes that are not apparent in overt responses but still may be detected via response time patterns. We propose a method for modeling response times as a mixture of Gaussians, adapting the strong-consensus model of cultural mixture modeling to model this implicit measure of knowledge strength. We report the results of two behavioral experiments and one simulation experiment that establish the usefulness of the approach, as well as some of the boundary conditions under which distinct groups of shared agreement might be recovered, even when the group identity is not known. The results reveal that the ability to recover and identify shared-belief groups depends on (1) the level of noise in the measurement, (2) the differential signals for strong versus weak attitudes, and (3) the similarity between group attitudes. Consequently, the method shows promise for identifying latent groups among a population whose overt attitudes do not differ, but whose implicit or covert attitudes or knowledge may differ.

Hot isostatic pressing (HIP) of powder mixtures and composites: Packing, densification, and microstructural effects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, E.K.H.; Funkenbusch, P.D.

1993-06-01

Hot isostatic pressing (HIP) of powder mixtures (containing differently sized components) and of composite powders is analyzed. Recent progress, including development of a simple scheme for estimating radial distribution functions, has made modeling of these systems practical. Experimentally, powders containing bimodal or continuous size distributions are observed to hot isostatically press to a higher density tinder identical processing conditions and to show large differences in the densification rate as a function of density when compared with the monosize powders usually assumed for modeling purposes. Modeling correctly predicts these trends and suggests that they can be partially, but not entirely, attributedmore » to initial packing density differences. Modeling also predicts increased deformation in the smaller particles within a mixture. This effect has also been observed experimentally and is associated with microstructural changes, such as preferential recrystallization of small particles. Finally, consolidation of a composite mixture containing hard, but deformable, inclusions has been modeled for comparison with existing experimental data. Modeling results match both the densification and microstructural observations reported experimentally. Densification is retarded due to contacts between the reinforcing particles which support a significant portion of the applied pressure. In addition, partitioning of deformation between soft matrix and hard inclusion powders results in increased deformation of the softer material.« less

Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures.

PubMed

Hegazy, Maha A; Lotfy, Hayam M; Mowaka, Shereen; Mohamed, Ekram Hany

2016-07-05

Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations. Copyright © 2016 Elsevier B.V. All rights reserved.

The Cusp Catastrophe Model as Cross-Sectional and Longitudinal Mixture Structural Equation Models

PubMed Central

Chow, Sy-Miin; Witkiewitz, Katie; Grasman, Raoul P. P. P.; Maisto, Stephen A.

2015-01-01

Catastrophe theory (Thom, 1972, 1993) is the study of the many ways in which continuous changes in a system’s parameters can result in discontinuous changes in one or several outcome variables of interest. Catastrophe theory–inspired models have been used to represent a variety of change phenomena in the realm of social and behavioral sciences. Despite their promise, widespread applications of catastrophe models have been impeded, in part, by difficulties in performing model fitting and model comparison procedures. We propose a new modeling framework for testing one kind of catastrophe model — the cusp catastrophe model — as a mixture structural equation model (MSEM) when cross-sectional data are available; or alternatively, as an MSEM with regime-switching (MSEM-RS) when longitudinal panel data are available. The proposed models and the advantages offered by this alternative modeling framework are illustrated using two empirical examples and a simulation study. PMID:25822209

DCMDN: Deep Convolutional Mixture Density Network

NASA Astrophysics Data System (ADS)

D'Isanto, Antonio; Polsterer, Kai Lars

2017-09-01

Deep Convolutional Mixture Density Network (DCMDN) estimates probabilistic photometric redshift directly from multi-band imaging data by combining a version of a deep convolutional network with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) are applied as performance criteria. DCMDN is able to predict redshift PDFs independently from the type of source, e.g. galaxies, quasars or stars and renders pre-classification of objects and feature extraction unnecessary; the method is extremely general and allows the solving of any kind of probabilistic regression problems based on imaging data, such as estimating metallicity or star formation rate in galaxies.

Bayesian mixture modeling for blood sugar levels of diabetes mellitus patients (case study in RSUD Saiful Anwar Malang Indonesia)

NASA Astrophysics Data System (ADS)

Budi Astuti, Ani; Iriawan, Nur; Irhamah; Kuswanto, Heri; Sasiarini, Laksmi

2017-10-01

Bayesian statistics proposes an approach that is very flexible in the number of samples and distribution of data. Bayesian Mixture Model (BMM) is a Bayesian approach for multimodal models. Diabetes Mellitus (DM) is more commonly known in the Indonesian community as sweet pee. This disease is one type of chronic non-communicable diseases but it is very dangerous to humans because of the effects of other diseases complications caused. WHO reports in 2013 showed DM disease was ranked 6th in the world as the leading causes of human death. In Indonesia, DM disease continues to increase over time. These research would be studied patterns and would be built the BMM models of the DM data through simulation studies where the simulation data built on cases of blood sugar levels of DM patients in RSUD Saiful Anwar Malang. The results have been successfully demonstrated pattern of distribution of the DM data which has a normal mixture distribution. The BMM models have succeed to accommodate the real condition of the DM data based on the data driven concept.

Model of Fluidized Bed Containing Reacting Solids and Gases

NASA Technical Reports Server (NTRS)

Bellan, Josette; Lathouwers, Danny

2003-01-01

A mathematical model has been developed for describing the thermofluid dynamics of a dense, chemically reacting mixture of solid particles and gases. As used here, "dense" signifies having a large volume fraction of particles, as for example in a bubbling fluidized bed. The model is intended especially for application to fluidized beds that contain mixtures of carrier gases, biomass undergoing pyrolysis, and sand. So far, the design of fluidized beds and other gas/solid industrial processing equipment has been based on empirical correlations derived from laboratory- and pilot-scale units. The present mathematical model is a product of continuing efforts to develop a computational capability for optimizing the designs of fluidized beds and related equipment on the basis of first principles. Such a capability could eliminate the need for expensive, time-consuming predesign testing.

PLUME-MoM 1.0: a new 1-D model of volcanic plumes based on the method of moments

NASA Astrophysics Data System (ADS)

de'Michieli Vitturi, M.; Neri, A.; Barsotti, S.

2015-05-01

In this paper a new mathematical model for volcanic plumes, named PlumeMoM, is presented. The model describes the steady-state 1-D dynamics of the plume in a 3-D coordinate system, accounting for continuous variability in particle distribution of the pyroclastic mixture ejected at the vent. Volcanic plumes are composed of pyroclastic particles of many different sizes ranging from a few microns up to several centimeters and more. Proper description of such a multiparticle nature is crucial when quantifying changes in grain-size distribution along the plume and, therefore, for better characterization of source conditions of ash dispersal models. The new model is based on the method of moments, which allows description of the pyroclastic mixture dynamics not only in the spatial domain but also in the space of properties of the continuous size-distribution of the particles. This is achieved by formulation of fundamental transport equations for the multiparticle mixture with respect to the different moments of the grain-size distribution. Different formulations, in terms of the distribution of the particle number, as well as of the mass distribution expressed in terms of the Krumbein log scale, are also derived. Comparison between the new moments-based formulation and the classical approach, based on the discretization of the mixture in N discrete phases, shows that the new model allows the same results to be obtained with a significantly lower computational cost (particularly when a large number of discrete phases is adopted). Application of the new model, coupled with uncertainty quantification and global sensitivity analyses, enables investigation of the response of four key output variables (mean and standard deviation (SD) of the grain-size distribution at the top of the plume, plume height and amount of mass lost by the plume during the ascent) to changes in the main input parameters (mean and SD) characterizing the pyroclastic mixture at the base of the plume. Results show that, for the range of parameters investigated, the grain-size distribution at the top of the plume is remarkably similar to that at the base and that the plume height is only weakly affected by the parameters of the grain distribution.

Investigation into the performance of different models for predicting stutter.

PubMed

Bright, Jo-Anne; Curran, James M; Buckleton, John S

2013-07-01

In this paper we have examined five possible models for the behaviour of the stutter ratio, SR. These were two log-normal models, two gamma models, and a two-component normal mixture model. A two-component normal mixture model was chosen with different behaviours of variance; at each locus SR was described with two distributions, both with the same mean. The distributions have difference variances: one for the majority of the observations and a second for the less well-behaved ones. We apply each model to a set of known single source Identifiler™, NGM SElect™ and PowerPlex(®) 21 DNA profiles to show the applicability of our findings to different data sets. SR determined from the single source profiles were compared to the calculated SR after application of the models. The model performance was tested by calculating the log-likelihoods and comparing the difference in Akaike information criterion (AIC). The two-component normal mixture model systematically outperformed all others, despite the increase in the number of parameters. This model, as well as performing well statistically, has intuitive appeal for forensic biologists and could be implemented in an expert system with a continuous method for DNA interpretation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Formulation, Implementation and Validation of a Two-Fluid model in a Fuel Cell CFD Code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jain, Kunal; Cole, J. Vernon; Kumar, Sanjiv

2008-12-01

Water management is one of the main challenges in PEM Fuel Cells. While water is essential for membrane electrical conductivity, excess liquid water leads to flooding of catalyst layers. Despite the fact that accurate prediction of two-phase transport is key for optimal water management, understanding of the two-phase transport in fuel cells is relatively poor. Wang et. al. have studied the two-phase transport in the channel and diffusion layer separately using a multiphase mixture model. The model fails to accurately predict saturation values for high humidity inlet streams. Nguyen et. al. developed a two-dimensional, two-phase, isothermal, isobaric, steady state modelmore » of the catalyst and gas diffusion layers. The model neglects any liquid in the channel. Djilali et. al. developed a three-dimensional two-phase multicomponent model. The model is an improvement over previous models, but neglects drag between the liquid and the gas phases in the channel. In this work, we present a comprehensive two-fluid model relevant to fuel cells. Models for two-phase transport through Channel, Gas Diffusion Layer (GDL) and Channel-GDL interface, are discussed. In the channel, the gas and liquid pressures are assumed to be same. The surface tension effects in the channel are incorporated using the continuum surface force (CSF) model. The force at the surface is expressed as a volumetric body force and added as a source to the momentum equation. In the GDL, the gas and liquid are assumed to be at different pressures. The difference in the pressures (capillary pressure) is calculated using an empirical correlations. At the Channel-GDL interface, the wall adhesion affects need to be taken into account. SIMPLE-type methods recast the continuity equation into a pressure-correction equation, the solution of which then provides corrections for velocities and pressures. However, in the two-fluid model, the presence of two phasic continuity equations gives more freedom and more complications. A general approach would be to form a mixture continuity equation by linearly combining the phasic continuity equations using appropriate weighting factors. Analogous to mixture equation for pressure correction, a difference equation is used for the volume/phase fraction by taking the difference between the phasic continuity equations. The relative advantages of the above mentioned algorithmic variants for computing pressure correction and volume fractions are discussed and quantitatively assessed. Preliminary model validation is done for each component of the fuel cell. The two-phase transport in the channel is validated using empirical correlations. Transport in the GDL is validated against results obtained from LBM and VOF simulation techniques. The Channel-GDL interface transport will be validated against experiment and empirical correlation of droplet detachment at the interface.« less

Prediction of Agglomeration, Fouling, and Corrosion Tendency of Fuels in CFB Co-Combustion

NASA Astrophysics Data System (ADS)

Barišć, Vesna; Zabetta, Edgardo Coda; Sarkki, Juha

Prediction of agglomeration, fouling, and corrosion tendency of fuels is essential to the design of any CFB boiler. During the years, tools have been successfully developed at Foster Wheeler to help with such predictions for the most commercial fuels. However, changes in fuel market and the ever-growing demand for co-combustion capabilities pose a continuous need for development. This paper presents results from recently upgraded models used at Foster Wheeler to predict agglomeration, fouling, and corrosion tendency of a variety of fuels and mixtures. The models, subject of this paper, are semi-empirical computer tools that combine the theoretical basics of agglomeration/fouling/corrosion phenomena with empirical correlations. Correlations are derived from Foster Wheeler's experience in fluidized beds, including nearly 10,000 fuel samples and over 1,000 tests in about 150 CFB units. In these models, fuels are evaluated based on their classification, their chemical and physical properties by standard analyses (proximate, ultimate, fuel ash composition, etc.;.) alongside with Foster Wheeler own characterization methods. Mixtures are then evaluated taking into account the component fuels. This paper presents the predictive capabilities of the agglomeration/fouling/corrosion probability models for selected fuels and mixtures fired in full-scale. The selected fuels include coals and different types of biomass. The models are capable to predict the behavior of most fuels and mixtures, but also offer possibilities for further improvements.

Financial Data Analysis by means of Coupled Continuous-Time Random Walk in Rachev-Rűschendorf Model

NASA Astrophysics Data System (ADS)

Jurlewicz, A.; Wyłomańska, A.; Żebrowski, P.

2008-09-01

We adapt the continuous-time random walk formalism to describe asset price evolution. We expand the idea proposed by Rachev and Rűschendorf who analyzed the binomial pricing model in the discrete time with randomization of the number of price changes. As a result, in the framework of the proposed model we obtain a mixture of the Gaussian and a generalized arcsine laws as the limiting distribution of log-returns. Moreover, we derive an European-call-option price that is an extension of the Black-Scholes formula. We apply the obtained theoretical results to model actual financial data and try to show that the continuous-time random walk offers alternative tools to deal with several complex issues of financial markets.

An approach for modeling thermal destruction of hazardous wastes in circulating fluidized bed incinerator.

PubMed

Patil, M P; Sonolikar, R L

2008-10-01

This paper presents a detailed computational fluid dynamics (CFD) based approach for modeling thermal destruction of hazardous wastes in a circulating fluidized bed (CFB) incinerator. The model is based on Eular - Lagrangian approach in which gas phase (continuous phase) is treated in a Eularian reference frame, whereas the waste particulate (dispersed phase) is treated in a Lagrangian reference frame. The reaction chemistry hasbeen modeled through a mixture fraction/ PDF approach. The conservation equations for mass, momentum, energy, mixture fraction and other closure equations have been solved using a general purpose CFD code FLUENT4.5. Afinite volume method on a structured grid has been used for solution of governing equations. The model provides detailed information on the hydrodynamics (gas velocity, particulate trajectories), gas composition (CO, CO2, O2) and temperature inside the riser. The model also allows different operating scenarios to be examined in an efficient manner.

Monitoring and modeling of ultrasonic wave propagation in crystallizing mixtures

NASA Astrophysics Data System (ADS)

Marshall, T.; Challis, R. E.; Tebbutt, J. S.

2002-05-01

The utility of ultrasonic compression wave techniques for monitoring crystallization processes is investigated in a study of the seeded crystallization of copper II sulfate pentahydrate from aqueous solution. Simple models are applied to predict crystal yield, crystal size distribution and the changing nature of the continuous phase. A scattering model is used to predict the ultrasonic attenuation as crystallization proceeds. Experiments confirm that modeled attenuation is in agreement with measured results.

Fast mix table construction for material discretization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, S. R.

2013-07-01

An effective hybrid Monte Carlo-deterministic implementation typically requires the approximation of a continuous geometry description with a discretized piecewise-constant material field. The inherent geometry discretization error can be reduced somewhat by using material mixing, where multiple materials inside a discrete mesh voxel are homogenized. Material mixing requires the construction of a 'mix table,' which stores the volume fractions in every mixture so that multiple voxels with similar compositions can reference the same mixture. Mix table construction is a potentially expensive serial operation for large problems with many materials and voxels. We formulate an efficient algorithm to construct a sparse mixmore » table in O(number of voxels x log number of mixtures) time. The new algorithm is implemented in ADVANTG and used to discretize continuous geometries onto a structured Cartesian grid. When applied to an end-of-life MCNP model of the High Flux Isotope Reactor with 270 distinct materials, the new method improves the material mixing time by a factor of 100 compared to a naive mix table implementation. (authors)« less

Fast Mix Table Construction for Material Discretization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Seth R

2013-01-01

An effective hybrid Monte Carlo--deterministic implementation typically requires the approximation of a continuous geometry description with a discretized piecewise-constant material field. The inherent geometry discretization error can be reduced somewhat by using material mixing, where multiple materials inside a discrete mesh voxel are homogenized. Material mixing requires the construction of a ``mix table,'' which stores the volume fractions in every mixture so that multiple voxels with similar compositions can reference the same mixture. Mix table construction is a potentially expensive serial operation for large problems with many materials and voxels. We formulate an efficient algorithm to construct a sparse mix table inmore » $$O(\\text{number of voxels}\\times \\log \\text{number of mixtures})$$ time. The new algorithm is implemented in ADVANTG and used to discretize continuous geometries onto a structured Cartesian grid. When applied to an end-of-life MCNP model of the High Flux Isotope Reactor with 270 distinct materials, the new method improves the material mixing time by a factor of 100 compared to a naive mix table implementation.« less

An Alternative Model of Philanthropy

ERIC Educational Resources Information Center

Green, Madeleine F.; Bezbatchenko, Annie W.

2014-01-01

This article begins by observing that foundations come in all shapes and sizes. The mission and grant-making philosophy of any foundation are determined by an unscientific mixture of its history, changing external realities, and leaders. The article then continues by describing The Teagle Foundation, a small, philanthropic organization with about…

Bioethanol production optimization: a thermodynamic analysis.

PubMed

Alvarez, Víctor H; Rivera, Elmer Ccopa; Costa, Aline C; Filho, Rubens Maciel; Wolf Maciel, Maria Regina; Aznar, Martín

2008-03-01

In this work, the phase equilibrium of binary mixtures for bioethanol production by continuous extractive process was studied. The process is composed of four interlinked units: fermentor, centrifuge, cell treatment unit, and flash vessel (ethanol-congener separation unit). A proposal for modeling the vapor-liquid equilibrium in binary mixtures found in the flash vessel has been considered. This approach uses the Predictive Soave-Redlich-Kwong equation of state, with original and modified molecular parameters. The congeners considered were acetic acid, acetaldehyde, furfural, methanol, and 1-pentanol. The results show that the introduction of new molecular parameters r and q in the UNIFAC model gives more accurate predictions for the concentration of the congener in the gas phase for binary and ternary systems.

PLUME-MoM 1.0: A new integral model of volcanic plumes based on the method of moments

NASA Astrophysics Data System (ADS)

de'Michieli Vitturi, M.; Neri, A.; Barsotti, S.

2015-08-01

In this paper a new integral mathematical model for volcanic plumes, named PLUME-MoM, is presented. The model describes the steady-state dynamics of a plume in a 3-D coordinate system, accounting for continuous variability in particle size distribution of the pyroclastic mixture ejected at the vent. Volcanic plumes are composed of pyroclastic particles of many different sizes ranging from a few microns up to several centimeters and more. A proper description of such a multi-particle nature is crucial when quantifying changes in grain-size distribution along the plume and, therefore, for better characterization of source conditions of ash dispersal models. The new model is based on the method of moments, which allows for a description of the pyroclastic mixture dynamics not only in the spatial domain but also in the space of parameters of the continuous size distribution of the particles. This is achieved by formulation of fundamental transport equations for the multi-particle mixture with respect to the different moments of the grain-size distribution. Different formulations, in terms of the distribution of the particle number, as well as of the mass distribution expressed in terms of the Krumbein log scale, are also derived. Comparison between the new moments-based formulation and the classical approach, based on the discretization of the mixture in N discrete phases, shows that the new model allows for the same results to be obtained with a significantly lower computational cost (particularly when a large number of discrete phases is adopted). Application of the new model, coupled with uncertainty quantification and global sensitivity analyses, enables the investigation of the response of four key output variables (mean and standard deviation of the grain-size distribution at the top of the plume, plume height and amount of mass lost by the plume during the ascent) to changes in the main input parameters (mean and standard deviation) characterizing the pyroclastic mixture at the base of the plume. Results show that, for the range of parameters investigated and without considering interparticle processes such as aggregation or comminution, the grain-size distribution at the top of the plume is remarkably similar to that at the base and that the plume height is only weakly affected by the parameters of the grain distribution. The adopted approach can be potentially extended to the consideration of key particle-particle effects occurring in the plume including particle aggregation and fragmentation.

Transient thermohydraulic heat pipe modeling

NASA Astrophysics Data System (ADS)

Hall, Michael L.; Doster, Joseph M.

Many space based reactor designs employ heat pipes as a means of conveying heat. In these designs, thermal radiation is the principle means for rejecting waste heat from the reactor system, making it desirable to operate at high temperatures. Lithium is generally the working fluid of choice as it undergoes a liquid-vapor transformation at the preferred operating temperature. The nature of remote startup, restart, and reaction to threats necessitates an accurate, detailed transient model of the heat pipe operation. A model is outlined of the vapor core region of the heat pipe which is part of a large model of the entire heat pipe thermal response. The vapor core is modeled using the area averaged Navier-Stokes equations in one dimension, which take into account the effects of mass, energy and momentum transfer. The core model is single phase (gaseous), but contains two components: lithium gas and a noncondensible vapor. The vapor core model consists of the continuity equations for the mixture and noncondensible, as well as mixture equations for internal energy and momentum.

Unified Computational Methods for Regression Analysis of Zero-Inflated and Bound-Inflated Data

PubMed Central

Yang, Yan; Simpson, Douglas

2010-01-01

Bounded data with excess observations at the boundary are common in many areas of application. Various individual cases of inflated mixture models have been studied in the literature for bound-inflated data, yet the computational methods have been developed separately for each type of model. In this article we use a common framework for computing these models, and expand the range of models for both discrete and semi-continuous data with point inflation at the lower boundary. The quasi-Newton and EM algorithms are adapted and compared for estimation of model parameters. The numerical Hessian and generalized Louis method are investigated as means for computing standard errors after optimization. Correlated data are included in this framework via generalized estimating equations. The estimation of parameters and effectiveness of standard errors are demonstrated through simulation and in the analysis of data from an ultrasound bioeffect study. The unified approach enables reliable computation for a wide class of inflated mixture models and comparison of competing models. PMID:20228950

Boussinesq approximation of the Cahn-Hilliard-Navier-Stokes equations.

PubMed

Vorobev, Anatoliy

2010-11-01

We use the Cahn-Hilliard approach to model the slow dissolution dynamics of binary mixtures. An important peculiarity of the Cahn-Hilliard-Navier-Stokes equations is the necessity to use the full continuity equation even for a binary mixture of two incompressible liquids due to dependence of mixture density on concentration. The quasicompressibility of the governing equations brings a short time-scale (quasiacoustic) process that may not affect the slow dynamics but may significantly complicate the numerical treatment. Using the multiple-scale method we separate the physical processes occurring on different time scales and, ultimately, derive the equations with the filtered-out quasiacoustics. The derived equations represent the Boussinesq approximation of the Cahn-Hilliard-Navier-Stokes equations. This approximation can be further employed as a universal theoretical model for an analysis of slow thermodynamic and hydrodynamic evolution of the multiphase systems with strongly evolving and diffusing interfacial boundaries, i.e., for the processes involving dissolution/nucleation, evaporation/condensation, solidification/melting, polymerization, etc.

Application of Project Portfolio Management

NASA Astrophysics Data System (ADS)

Pankowska, Malgorzata

The main goal of the chapter is the presentation of the application project portfolio management approach to support development of e-Municipality and public administration information systems. The models of how people publish and utilize information on the web have been transformed continually. Instead of simply viewing on static web pages, users publish their own content through blogs and photo- and video-sharing slides. Analysed in this chapter, ICT (Information Communication Technology) projects for municipalities cover the mixture of the static web pages, e-Government information systems, and Wikis. So, for the management of the ICT projects' mixtures the portfolio project management approach is proposed.

A multiphase approach to model ultrafiltration of deformable colloids

NASA Astrophysics Data System (ADS)

Haribabu, Malavika; Dunstan, Dave; Davidson, Malcolm; Harvie, Dalton

2017-11-01

Ultrafiltration (UF) is widely used in the dairy industry to fractionate and concentrate proteins, during the manufacture of milk protein concentrate and cheese. The protein build-up, comprising casein micelles (CM) and whey proteins, at the membrane surface during UF increases the resistance of the membrane system, thereby decreasing the performance of the process unit. CM have a complex structure that hydrodynamically behaves as a hard-sphere when dilute, but deforms beyond the random packing limit, forming a shear-thinning gel. This study employs a mixture model, based on the mixture phase continuity, Navier-Stokes equations, and solids continuity equation, to predict the solid concentration and velocity distribution during UF of CM. Micelle deformation is modelled as a function of volume fraction and dependent on its elastic modulus and particle size. The effect of deformation on gel permeability is implemented via Happel's permeability for hard spheres. Under crossflow conditions, the gel thickness is observed to increase along the membrane length, followed by a decrease towards the end of the membrane, resulting in an increase in flux at the latter section of the membrane. This study demonstrates that the membrane end-effects are important in determining UF performance.

Co-digestion of solid waste: Towards a simple model to predict methane production.

PubMed

Kouas, Mokhles; Torrijos, Michel; Schmitz, Sabine; Sousbie, Philippe; Sayadi, Sami; Harmand, Jérôme

2018-04-01

Modeling methane production is a key issue for solid waste co-digestion. Here, the effect of a step-wise increase in the organic loading rate (OLR) on reactor performance was investigated, and four new models were evaluated to predict methane yields using data acquired in batch mode. Four co-digestion experiments of mixtures of 2 solid substrates were conducted in semi-continuous mode. Experimental methane yields were always higher than the BMP values of mixtures calculated from the BMP of each substrate, highlighting the importance of endogenous production (methane produced from auto-degradation of microbial community and generated solids). The experimental methane productions under increasing OLRs corresponded well to the modeled data using the model with constant endogenous production and kinetics identified at 80% from total batch time. This model provides a simple and useful tool for technical design consultancies and plant operators to optimize the co-digestion and the choice of the OLRs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial generalised linear mixed models based on distances.

PubMed

Melo, Oscar O; Mateu, Jorge; Melo, Carlos E

2016-10-01

Risk models derived from environmental data have been widely shown to be effective in delineating geographical areas of risk because they are intuitively easy to understand. We present a new method based on distances, which allows the modelling of continuous and non-continuous random variables through distance-based spatial generalised linear mixed models. The parameters are estimated using Markov chain Monte Carlo maximum likelihood, which is a feasible and a useful technique. The proposed method depends on a detrending step built from continuous or categorical explanatory variables, or a mixture among them, by using an appropriate Euclidean distance. The method is illustrated through the analysis of the variation in the prevalence of Loa loa among a sample of village residents in Cameroon, where the explanatory variables included elevation, together with maximum normalised-difference vegetation index and the standard deviation of normalised-difference vegetation index calculated from repeated satellite scans over time. © The Author(s) 2013.

Multisource Data Classification Using A Hybrid Semi-supervised Learning Scheme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vatsavai, Raju; Bhaduri, Budhendra L; Shekhar, Shashi

2009-01-01

In many practical situations thematic classes can not be discriminated by spectral measurements alone. Often one needs additional features such as population density, road density, wetlands, elevation, soil types, etc. which are discrete attributes. On the other hand remote sensing image features are continuous attributes. Finding a suitable statistical model and estimation of parameters is a challenging task in multisource (e.g., discrete and continuous attributes) data classification. In this paper we present a semi-supervised learning method by assuming that the samples were generated by a mixture model, where each component could be either a continuous or discrete distribution. Overall classificationmore » accuracy of the proposed method is improved by 12% in our initial experiments.« less

A menu-driven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis and density estimation.

PubMed

Karabatsos, George

2017-02-01

Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected functionals and values of covariates. The software is illustrated through the BNP regression analysis of real data.

Characterization of HMA mixtures containing high reclaimed asphalt pavement content with crumb rubber additives : [technical summary].

DOT National Transportation Integrated Search

2013-03-01

With the increase in hot mix asphalt (HMA) mixtures prices continuously climbing, highway agencies and owners are continually : searching for methods to decrease material costs and maximize their benefi ts with no compromise in performance. One su...

Phase-field modeling of mixing/demixing of regular binary mixtures with a composition-dependent viscosity

NASA Astrophysics Data System (ADS)

Lamorgese, A.; Mauri, R.

2017-04-01

We simulate the mixing (demixing) process of a quiescent binary liquid mixture with a composition-dependent viscosity which is instantaneously brought from the two-phase (one-phase) to the one-phase (two-phase) region of its phase diagram. Our theoretical approach follows a standard diffuse-interface model of partially miscible regular binary mixtures wherein convection and diffusion are coupled via a nonequilibrium capillary force, expressing the tendency of the phase-separating system to minimize its free energy. Based on 2D simulation results, we discuss the influence of viscosity ratio on basic statistics of the mixing (segregation) process triggered by a rapid heating (quench), assuming that the ratio of capillary to viscous forces (a.k.a. the fluidity coefficient) is large. We show that, for a phase-separating system, at a fixed value of the fluidity coefficient (with the continuous phase viscosity taken as a reference), the separation depth and the characteristic length of single-phase microdomains decrease monotonically for increasing values of the viscosity of the dispersed phase. This variation, however, is quite small, in agreement with experimental results. On the other hand, as one might expect, at a fixed viscosity of the dispersed phase both of the above statistics increase monotonically as the viscosity of the continuous phase decreases. Finally, we show that for a mixing system the attainment of a single-phase equilibrium state by coalescence and diffusion is retarded by an increase in the viscosity ratio at a fixed fluidity for the dispersed phase. In fact, for large enough values of the viscosity ratio, a thin film of the continuous phase becomes apparent when two drops of the minority phase approach each other, which further retards coalescence.

Chemical Mixtures Health Risk Assessment: Overview of Exposure Assessment, Whole Mixtures Assessments; Basic Concepts

EPA Science Inventory

This problems-based, half-day, introductory workshop focuses on methods to assess health risks posed by exposures to chemical mixtures in the environment. Chemical mixtures health risk assessment methods continue to be developed and evolve to address concerns over health risks f...

Xenon and Other Volatile Anesthetics Change Domain Structure in Model Lipid Raft Membranes

PubMed Central

Weinrich, Michael; Worcester, David L.

2014-01-01

Inhalation anesthetics have been in clinical use for over 160 years, but the molecular mechanisms of action continue to be investigated. Direct interactions with ion channels received much attention after it was found that anesthetics do not change the structure of homogeneous model membranes. However, it was recently found that halothane, a prototypical anesthetic, changes domain structure of a binary lipid membrane. The noble gas xenon is an excellent anesthetic and provides a pivotal test of the generality of this finding, extended to ternary lipid raft mixtures. We report that xenon and conventional anesthetics change the domain equilibrium in two canonical ternary lipid raft mixtures. These findings demonstrate a membrane-mediated mechanism whereby inhalation anesthetics can affect the lipid environment of trans-membrane proteins. PMID:24299622

Evaluation of Thermodynamic Models for Predicting Phase Equilibria of CO2 + Impurity Binary Mixture

NASA Astrophysics Data System (ADS)

Shin, Byeong Soo; Rho, Won Gu; You, Seong-Sik; Kang, Jeong Won; Lee, Chul Soo

2018-03-01

For the design and operation of CO2 capture and storage (CCS) processes, equation of state (EoS) models are used for phase equilibrium calculations. Reliability of an EoS model plays a crucial role, and many variations of EoS models have been reported and continue to be published. The prediction of phase equilibria for CO2 mixtures containing SO2, N2, NO, H2, O2, CH4, H2S, Ar, and H2O is important for CO2 transportation because the captured gas normally contains small amounts of impurities even though it is purified in advance. For the design of pipelines in deep sea or arctic conditions, flow assurance and safety are considered priority issues, and highly reliable calculations are required. In this work, predictive Soave-Redlich-Kwong, cubic plus association, Groupe Européen de Recherches Gazières (GERG-2008), perturbed-chain statistical associating fluid theory, and non-random lattice fluids hydrogen bond EoS models were compared regarding performance in calculating phase equilibria of CO2-impurity binary mixtures and with the collected literature data. No single EoS could cover the entire range of systems considered in this study. Weaknesses and strong points of each EoS model were analyzed, and recommendations are given as guidelines for safe design and operation of CCS processes.

Continuous plutonium dissolution apparatus

DOEpatents

Meyer, F.G.; Tesitor, C.N.

1974-02-26

This invention is concerned with continuous dissolution of metals such as plutonium. A high normality acid mixture is fed into a boiler vessel, vaporized, and subsequently condensed as a low normality acid mixture. The mixture is then conveyed to a dissolution vessel and contacted with the plutonium metal to dissolve the plutonium in the dissolution vessel, reacting therewith forming plutonium nitrate. The reaction products are then conveyed to the mixing vessel and maintained soluble by the high normality acid, with separation and removal of the desired constituent. (Official Gazette)

7 CFR 201.12a - Lawn and turf seed mixtures.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 3 2011-01-01 2011-01-01 false Lawn and turf seed mixtures. 201.12a Section 201.12a Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT REGULATIONS Labeling...

7 CFR 201.12a - Lawn and turf seed mixtures.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 3 2013-01-01 2013-01-01 false Lawn and turf seed mixtures. 201.12a Section 201.12a Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT REGULATIONS Labeling...

7 CFR 201.12a - Lawn and turf seed mixtures.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 3 2010-01-01 2010-01-01 false Lawn and turf seed mixtures. 201.12a Section 201.12a Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT REGULATIONS Labeling...

7 CFR 201.12a - Lawn and turf seed mixtures.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 3 2012-01-01 2012-01-01 false Lawn and turf seed mixtures. 201.12a Section 201.12a Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT REGULATIONS Labeling...

7 CFR 201.12a - Lawn and turf seed mixtures.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 3 2014-01-01 2014-01-01 false Lawn and turf seed mixtures. 201.12a Section 201.12a Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT REGULATIONS Labeling...

Experimental designs and risk assessment in combination toxicology: panel discussion.

PubMed

Henschler, D; Bolt, H M; Jonker, D; Pieters, M N; Groten, J P

1996-01-01

Advancing our knowledge on the toxicology of combined exposures to chemicals and implementation of this knowledge in guidelines for health risk assessment of such combined exposures are necessities dictated by the simple fact that humans are continuously exposed to a multitude of chemicals. A prerequisite for successful research and fruitful discussions on the toxicology of combined exposures (mixtures of chemicals) is the use of defined terminology implemented by an authoritative international body such as, for example, the International Union of Pure and Applied Chemistry (IUPAC) Toxicology Committee. The extreme complexity of mixture toxicology calls for new research methodologies to study interactive effects, taking into account limited resources. Of these methodologies, statistical designs and mathematical modelling of toxicokinetics and toxicodynamics seem to be most promising. Emphasis should be placed on low-dose modelling and experimental validation. The scientifically sound so-called bottom-up approach should be supplemented with more pragmatic approaches, focusing on selection of the most hazardous chemicals in a mixture and careful consideration of the mode of action and possible interactive effects of these chemicals. Pragmatic approaches may be of particular importance to study and evaluate complex mixtures; after identification of the 'top ten' (most risky) chemicals in the mixture they can be examined and evaluated as a defined (simple) chemical mixture. In setting exposure limits for individual chemicals, the use of an additional safety factor to compensate for potential increased risk due to simultaneous exposure to other chemicals, has no clear scientific justification. The use of such an additional factor is a political rather than a scientific choice.

Testing treatment effect in schizophrenia clinical trials with heavy patient dropout using latent class growth mixture models.

PubMed

Kong, Fanhui; Chen, Yeh-Fong

2016-07-01

By examining the outcome trajectories of the dropout patients with different reasons in the schizophrenia trials, we note that although patients are recruited from the same protocol that have compatible baseline characteristics, they may respond differently even to the same treatment. Some patients show consistent improvement while others only have temporary relief. This creates different patient subpopulations characterized by their response and dropout patterns. At the same time, those who continue to improve seem to be more likely to complete the study while those who only experience temporary relief have a higher chance to drop out. Such phenomenon appears to be quite general in schizophrenia clinical trials. This simultaneous inhomogeneity both in patient response as well as dropout patterns creates a scenario of missing not at random and therefore results in biases when we use the statistical methods based on the missing at random assumption to test treatment efficacy. In this paper, we propose to use the latent class growth mixture model, which is a special case of the latent mixture model, to conduct the statistical analyses in such situation. This model allows us to take the inhomogeneity among subpopulations into consideration to make more accurate inferences on the treatment effect at any visit time. Comparing with the conventional statistical methods such as mixed-effects model for repeated measures, we demonstrate through simulations that the proposed latent mixture model approach gives better control on the Type I error rate in testing treatment effect. Published 2016. This article is a U.S. Government work and is in the public domain in the USA. Copyright © 2016 John Wiley & Sons, Ltd.

Impact of Lead Time and Safety Factor in Mixed Inventory Models with Backorder Discounts

NASA Astrophysics Data System (ADS)

Lo, Ming-Cheng; Chao-Hsien Pan, Jason; Lin, Kai-Cing; Hsu, Jia-Wei

This study investigates the impact of safety factor on the continuous review inventory model involving controllable lead time with mixture of backorder discount and partial lost sales. The objective is to minimize the expected total annual cost with respect to order quantity, backorder price discount, safety factor and lead time. A model with normal demand is also discussed. Numerical examples are presented to illustrate the procedures of the algorithms and the effects of parameters on the result of the proposed models are analyzed.

Mixture toxicity of flubendazole and fenbendazole to Daphnia magna.

PubMed

Puckowski, Alan; Stolte, Stefan; Wagil, Marta; Markiewicz, Marta; Łukaszewicz, Paulina; Stepnowski, Piotr; Białk-Bielińska, Anna

2017-05-01

Nowadays, residual amounts of many pharmaceuticals can be found in various environmental compartments including surface and ground waters, soils and sediments as well as biota. Even though they undergo degradability, their environmental discharge is relatively continuous, thus they may be regarded as quasi-persistent contaminants, and are also frequently regarded as emerging organic pollutants. Benzimidazoles, especially flubendazole (FLU) and fenbendazole (FEN), represent two anthelmintic drugs belonging to this group. Although their presence in environmental matrices has been reported, there is relatively little data concerning their (eco)toxicological impact. Furthermore, no data is available on their mixture toxicity. FLU and FEN have been found to have a strong impact on an environmentally important non-target organism - Daphnia magna. Moreover, these compounds are usually present in the environment as a part of pharmaceutical mixtures. Therefore, there is a need to evaluate their mixture toxicity, which was the main aim of this study. Single substance toxicity tests were carried out in parallel with mixture studies of FLU and FEN, with the application of two well established concepts of Concentration Addition (CA) and Independent Action (IA). As a result, both models (CA and IA) were found to underestimate the toxicity of mixtures, however CA yielded more accurate predictions. Copyright © 2017 Elsevier GmbH. All rights reserved.

Mixture toxicity of six sulfonamides and their two transformation products to green algae Scenedesmus vacuolatus and duckweed Lemna minor.

PubMed

Białk-Bielińska, Anna; Caban, Magda; Pieczyńska, Aleksandra; Stepnowski, Piotr; Stolte, Stefan

2017-04-01

Since humans and ecosystems are continually exposed to a very complex and permanently changing mixture of chemicals, there is increasing concern in the general public about the potential adverse effects they may cause. Among all "emerging pollutants", pharmaceuticals in particular have raised great environmental concern. For these reasons the aim of our study was to evaluate the mixture toxicity of six antimicrobial sulfonamides (SAs) and their two most commonly identified degradation products - sulfanilic acid (SNA) and sulfanilamide (SN) - to limnic green algae Scenedesmus vacuolatus and duckweed Lemna minor. The ecotoxicological data for the single toxicity of SNA and SN towards selected organisms are presented. The concept of Concentration Addition (CA) was applied to estimate the effects, and less than additive effects were observed. In general terms, it seems sufficiently precautionary for the aquatic environment to consider the toxicity of a sulfonamide mixture as additive. The Concentration Addition model proves to be a reasonable worst-case estimation. Such a comparative study on the mixture toxicity of sulfonamides and their transformation products has been presented for the first time. Copyright © 2017 Elsevier Ltd. All rights reserved.

Discharge flow of a granular media from a silo: effect of the packing fraction and of the hopper angle

NASA Astrophysics Data System (ADS)

Benyamine, Mebirika; Aussillous, Pascale; Dalloz-Dubrujeaud, Blanche

2017-06-01

Silos are widely used in the industry. While empirical predictions of the flow rate, based on scaling laws, have existed for more than a century (Hagen 1852, translated in [1] - Beverloo et al. [2]), recent advances have be made on the understanding of the control parameters of the flow. In particular, using continuous modeling together with a mu(I) granular rheology seem to be successful in predicting the flow rate for large numbers of beads at the aperture (Staron et al.[3], [4]). Moreover Janda et al.[5] have shown that the packing fraction at the outlet plays an important role when the number of beads at the apeture decreases. Based on these considerations, we have studied experimentally the discharge flow of a granular media from a rectangular silo. We have varied two main parameters: the angle of the hopper, and the bulk packing fraction of the granular material by using bidisperse mixtures. We propose a simple physical model to describe the effect of these parameters, considering a continuous granular media with a dilatancy law at the outlet. This model predicts well the dependance of the flow rate on the hopper angle as well as the dependance of the flow rate on the fine mass fraction of a bidisperse mixture.

Continious production of exfoliated graphite composite compositions and flow field plates

DOEpatents

Shi, Jinjun; Zhamu, Aruna; Jang, Bor Z.

2010-07-20

A process of continuously producing a more isotropic, electrically conductive composite composition is provided. The process comprises: (a) continuously supplying a compressible mixture comprising exfoliated graphite worms and a binder or matrix material, wherein the binder or matrix material is in an amount of between 3% and 60% by weight based on the total weight of the mixture; (b) continuously compressing the compressible mixture at a pressure within the range of from about 5 psi or 0.035 MPa to about 50,000 psi or 350 MPa in at least a first direction into a cohered graphite composite compact; and (c) continuously compressing the composite compact in a second direction, different from the first direction, to form the composite composition in a sheet or plate form. The process leads to composite plates with exceptionally high thickness-direction electrical conductivity.

Four-way coupling of a three-dimensional debris flow solver to a Lagrangian Particle Simulation: method and first results

NASA Astrophysics Data System (ADS)

von Boetticher, Albrecht; Rickenmann, Dieter; McArdell, Brian; Kirchner, James W.

2017-04-01

Debris flows are dense flowing mixtures of water, clay, silt, sand and coarser particles. They are a common natural hazard in mountain regions and frequently cause severe damage. Modeling debris flows to design protection measures is still challenging due to the complex interactions within the inhomogeneous material mixture, and the sensitivity of the flow process to the channel geometry. The open-source, OpenFOAM-based finite-volume debris flow model debrisInterMixing (von Boetticher et al, 2016) defines rheology parameters based on the material properties of the debris flow mixture to reduce the number of free model parameters. As a simplification in this first model version, gravel was treated as a Coulomb-viscoplastic fluid, neglecting grain-to-grain collisions and the coupling between the coarser gravel grains and the interstitial fluid. Here we present an extension of that solver, accounting for the particle-to-particle and particle-to-boundary contacts with a Lagrangian Particle Simulation composed of spherical grains and a user-defined grain size distribution. The grain collisions of the Lagrangian particles add granular flow behavior to the finite-volume simulation of the continuous phases. The two-way coupling exchanges momentum between the phase-averaged flow in a finite volume cell, and among all individual particles contained in that cell, allowing the user to choose from a number of different drag models. The momentum exchange is implemented in the momentum equation and in the pressure equation (ensuring continuity) of the so-called PISO-loop, resulting in a stable 4-way coupling (particle-to-particle, particle-to-boundary, particle-to-fluid and fluid-to-particle) that represents the granular and viscous flow behavior of debris flow material. We will present simulations that illustrate the relative benefits and drawbacks of explicitly representing grain collisions, compared to the original debrisInterMixing solver.

Triggering Excimer Lasers by Photoionization from Corona Discharges

NASA Astrophysics Data System (ADS)

Xiong, Zhongmin; Duffey, Thomas; Brown, Daniel; Kushner, Mark

2009-10-01

High repetition rate ArF (192 nm) excimer lasers are used for photolithography sources in microelectronics fabrication. In highly attaching gas mixtures, preionization is critical to obtaining stable, reproducible glow discharges. Photoionization from a separate corona discharge is one technique for preionization which triggers the subsequent electron avalanche between the main electrodes. Photoionization triggering of an ArF excimer laser sustained in multi-atmosphere Ne/Ar/F2/Xe gas mixtures has been investigated using a 2-dimensional plasma hydrodynamics model including radiation transport. Continuity equations for charged and neutral species, and Poisson's equation are solved coincident with the electron temperature with transport coefficients obtained from solutions of Boltzmann's equation. Photoionizing radiation is produced by a surface discharge which propagates along a corona-bar located adjacent to the discharge electrodes. The consequences of pulse power waveform, corona bar location, capacitance and gas mixture on uniformity, symmetry and gain of the avalanche discharge will be discussed.

Acute toxicity to goldfish of mixtures of chloramines, copper, and linear alkylate sulfonate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsai, C.F.; McKee, J.A.

1980-01-01

The toxicity to goldfish (Carassius auratus) of mixtures of chloramines, copper, and linear alkylate sulfonate (LAS) was studied by continuous-flow toxicity tests during an exposure period of 96 hours. The individual toxicities of these three chemicals are either additive or synergistic in mixtures, depending on the rate of toxic action of the individual chemical, the toxicity ratio of the chemicals in the mixtures, and the concentration of the mixtures.

Research on gait-based human identification

NASA Astrophysics Data System (ADS)

Li, Youguo

Gait recognition refers to automatic identification of individual based on his/her style of walking. This paper proposes a gait recognition method based on Continuous Hidden Markov Model with Mixture of Gaussians(G-CHMM). First, we initialize a Gaussian mix model for training image sequence with K-means algorithm, then train the HMM parameters using a Baum-Welch algorithm. These gait feature sequences can be trained and obtain a Continuous HMM for every person, therefore, the 7 key frames and the obtained HMM can represent each person's gait sequence. Finally, the recognition is achieved by Front algorithm. The experiments made on CASIA gait databases obtain comparatively high correction identification ratio and comparatively strong robustness for variety of bodily angle.

Chemical Mixtures Health Risk Assessment of Environmental Contaminants: Concepts, Methods, Applications

EPA Science Inventory

This problems-based, introductory workshop focuses on methods to assess health risks posed by exposures to chemical mixtures in the environment. Chemical mixtures health risk assessment methods continue to be developed and evolve to address concerns over health risks from multic...

Chemical Mixtures Health Risk Assessment of Environmental Contaminants: Concepts, Methods, And Applications

EPA Science Inventory

This problems-based, introductory workshop focuses on methods to assess health risks posed by exposures to chemical mixtures in the environment. Chemical mixtures health risk assessment methods continue to be developed and evolve to address concerns over health risks from multic...

TMA Navigator: network inference, patient stratification and survival analysis with tissue microarray data

PubMed Central

Lubbock, Alexander L. R.; Katz, Elad; Harrison, David J.; Overton, Ian M.

2013-01-01

Tissue microarrays (TMAs) allow multiplexed analysis of tissue samples and are frequently used to estimate biomarker protein expression in tumour biopsies. TMA Navigator (www.tmanavigator.org) is an open access web application for analysis of TMA data and related information, accommodating categorical, semi-continuous and continuous expression scores. Non-biological variation, or batch effects, can hinder data analysis and may be mitigated using the ComBat algorithm, which is incorporated with enhancements for automated application to TMA data. Unsupervised grouping of samples (patients) is provided according to Gaussian mixture modelling of marker scores, with cardinality selected by Bayesian information criterion regularization. Kaplan–Meier survival analysis is available, including comparison of groups identified by mixture modelling using the Mantel-Cox log-rank test. TMA Navigator also supports network inference approaches useful for TMA datasets, which often constitute comparatively few markers. Tissue and cell-type specific networks derived from TMA expression data offer insights into the molecular logic underlying pathophenotypes, towards more effective and personalized medicine. Output is interactive, and results may be exported for use with external programs. Private anonymous access is available, and user accounts may be generated for easier data management. PMID:23761446

Chemistry of the outer planets: Investigations of the chemical nature of the atmosphere of Titan

NASA Technical Reports Server (NTRS)

Scattergood, Thomas W.

1985-01-01

It is clear from the experiments that a variety of complex organic models can be produced by lightning in a Titan-like gas mixture. The dominant products were found to be acetylene and hydrogen cyanide, with smaller amounts of many other species. Any aerosol produced by lightning inititated process will consist of a complex mixture of organic compounds, many of which should easily be identified by pyrolytic gas chromatography. Work will continue to expand the data base of molecules produced by lightning and other processes in order to assist in the design of appropriate analytical instruments for the upcoming Saturn/Titan mission and any other planetary probes.

Chemical Mixtures Health Risk Assessment of Environmental Contaminants: Concepts, Methods, Applications: Handbook

EPA Science Inventory

This problems-based, half-day, introductory workshop focuses on methods to assess health risks posed by exposures to chemical mixtures in the environment. Chemical mixtures health risk assessment methods continue to be developed and evolve to address concerns over health risks f...

Poisson Mixture Regression Models for Heart Disease Prediction.

PubMed

Mufudza, Chipo; Erol, Hamza

2016-01-01

Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.

Poisson Mixture Regression Models for Heart Disease Prediction

PubMed Central

Erol, Hamza

2016-01-01

Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611

A New Self-Consistent Field Model of Polymer/Nanoparticle Mixture

NASA Astrophysics Data System (ADS)

Chen, Kang; Li, Hui-Shu; Zhang, Bo-Kai; Li, Jian; Tian, Wen-De

2016-02-01

Field-theoretical method is efficient in predicting assembling structures of polymeric systems. However, it’s challenging to generalize this method to study the polymer/nanoparticle mixture due to its multi-scale nature. Here, we develop a new field-based model which unifies the nanoparticle description with the polymer field within the self-consistent field theory. Instead of being “ensemble-averaged” continuous distribution, the particle density in the final morphology can represent individual particles located at preferred positions. The discreteness of particle density allows our model to properly address the polymer-particle interface and the excluded-volume interaction. We use this model to study the simplest system of nanoparticles immersed in the dense homopolymer solution. The flexibility of tuning the interfacial details allows our model to capture the rich phenomena such as bridging aggregation and depletion attraction. Insights are obtained on the enthalpic and/or entropic origin of the structural variation due to the competition between depletion and interfacial interaction. This approach is readily extendable to the study of more complex polymer-based nanocomposites or biology-related systems, such as dendrimer/drug encapsulation and membrane/particle assembly.

A New Model for Simulating Gas Metal Arc Welding based on Phase Field Model

NASA Astrophysics Data System (ADS)

Jiang, Yongyue; Li, Li; Zhao, Zhijiang

2017-11-01

Lots of physical process, such as metal melting, multiphase fluids flow, heat and mass transfer and thermocapillary effect (Marangoni) and so on, will occur in gas metal arc welding (GMAW) which should be considered as a mixture system. In this paper, based on the previous work, we propose a new model to simulate GMAW including Navier-Stokes equation, the phase field model and energy equation. Unlike most previous work, we take the thermocapillary effect into the phase field model considering mixture energy which is different of volume of fluid method (VOF) widely used in GMAW before. We also consider gravity, electromagnetic force, surface tension, buoyancy effect and arc pressure in momentum equation. The spray transfer especially the projected transfer in GMAW is computed as numerical examples with a continuous finite element method and a modified midpoint scheme. Pulse current is set as welding current as the numerical example to show the numerical simulation of metal transfer which fits the theory of GMAW well. From the result compared with the data of high-speed photography and VOF model, the accuracy and stability of the model and scheme are easily validated and also the new model has the higher precieion.

The effect of binary mixtures of zinc, copper, cadmium, and nickel on the growth of the freshwater diatom Navicula pelliculosa and comparison with mixture toxicity model predictions.

PubMed

Nagai, Takashi; De Schamphelaere, Karel A C

2016-11-01

The authors investigated the effect of binary mixtures of zinc (Zn), copper (Cu), cadmium (Cd), and nickel (Ni) on the growth of a freshwater diatom, Navicula pelliculosa. A 7 × 7 full factorial experimental design (49 combinations in total) was used to test each binary metal mixture. A 3-d fluorescence microplate toxicity assay was used to test each combination. Mixture effects were predicted by concentration addition and independent action models based on a single-metal concentration-response relationship between the relative growth rate and the calculated free metal ion activity. Although the concentration addition model predicted the observed mixture toxicity significantly better than the independent action model for the Zn-Cu mixture, the independent action model predicted the observed mixture toxicity significantly better than the concentration addition model for the Cd-Zn, Cd-Ni, and Cd-Cu mixtures. For the Zn-Ni and Cu-Ni mixtures, it was unclear which of the 2 models was better. Statistical analysis concerning antagonistic/synergistic interactions showed that the concentration addition model is generally conservative (with the Zn-Ni mixture being the sole exception), indicating that the concentration addition model would be useful as a method for a conservative first-tier screening-level risk analysis of metal mixtures. Environ Toxicol Chem 2016;35:2765-2773. © 2016 SETAC. © 2016 SETAC.

Mixture Rasch Models with Joint Maximum Likelihood Estimation

ERIC Educational Resources Information Center

Willse, John T.

2011-01-01

This research provides a demonstration of the utility of mixture Rasch models. Specifically, a model capable of estimating a mixture partial credit model using joint maximum likelihood is presented. Like the partial credit model, the mixture partial credit model has the beneficial feature of being appropriate for analysis of assessment data…

Monthly streamflow forecasting based on hidden Markov model and Gaussian Mixture Regression

NASA Astrophysics Data System (ADS)

Liu, Yongqi; Ye, Lei; Qin, Hui; Hong, Xiaofeng; Ye, Jiajun; Yin, Xingli

2018-06-01

Reliable streamflow forecasts can be highly valuable for water resources planning and management. In this study, we combined a hidden Markov model (HMM) and Gaussian Mixture Regression (GMR) for probabilistic monthly streamflow forecasting. The HMM is initialized using a kernelized K-medoids clustering method, and the Baum-Welch algorithm is then executed to learn the model parameters. GMR derives a conditional probability distribution for the predictand given covariate information, including the antecedent flow at a local station and two surrounding stations. The performance of HMM-GMR was verified based on the mean square error and continuous ranked probability score skill scores. The reliability of the forecasts was assessed by examining the uniformity of the probability integral transform values. The results show that HMM-GMR obtained reasonably high skill scores and the uncertainty spread was appropriate. Different HMM states were assumed to be different climate conditions, which would lead to different types of observed values. We demonstrated that the HMM-GMR approach can handle multimodal and heteroscedastic data.

Recovery of lactic acid from the pretreated fermentation broth based on a novel hyper-cross-linked meso-micropore resin: Modeling.

PubMed

Song, Mingkai; Jiao, Pengfei; Qin, Taotao; Jiang, Kangkang; Zhou, Jingwei; Zhuang, Wei; Chen, Yong; Liu, Dong; Zhu, Chenjie; Chen, Xiaochun; Ying, Hanjie; Wu, Jinglan

2017-10-01

An innovative benign process for recovery lactic acid from its fermentation broth is proposed using a novel hyper-cross-linked meso-micropore resin and water as eluent. This work focuses on modeling the competitive adsorption behaviors of glucose, lactic acid and acetic acid ternary mixture and explosion of the adsorption mechanism. The characterization results showed the resin had a large BET surface area and specific pore structure with hydrophobic properties. By analysis of the physicochemical properties of the solutes and the resin, the mechanism of the separation is proposed as hydrophobic effect and size-exclusion. Subsequently three chromatographic models were applied to predict the competitive breakthrough curves of the ternary mixture under different operating conditions. The pore diffusion was the major limiting factor for the adsorption process, which was consistent with the BET results. The novel HD-06 resin can be a good potential adsorbent for the future SMB continuous separation process. Copyright © 2017 Elsevier Ltd. All rights reserved.

Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry

PubMed Central

Polanski, Andrzej; Marczyk, Michal; Pietrowska, Monika; Widlak, Piotr; Polanska, Joanna

2015-01-01

Mixture - modeling of mass spectra is an approach with many potential applications including peak detection and quantification, smoothing, de-noising, feature extraction and spectral signal compression. However, existing algorithms do not allow for automated analyses of whole spectra. Therefore, despite highlighting potential advantages of mixture modeling of mass spectra of peptide/protein mixtures and some preliminary results presented in several papers, the mixture modeling approach was so far not developed to the stage enabling systematic comparisons with existing software packages for proteomic mass spectra analyses. In this paper we present an efficient algorithm for Gaussian mixture modeling of proteomic mass spectra of different types (e.g., MALDI-ToF profiling, MALDI-IMS). The main idea is automated partitioning of protein mass spectral signal into fragments. The obtained fragments are separately decomposed into Gaussian mixture models. The parameters of the mixture models of fragments are then aggregated to form the mixture model of the whole spectrum. We compare the elaborated algorithm to existing algorithms for peak detection and we demonstrate improvements of peak detection efficiency obtained by using Gaussian mixture modeling. We also show applications of the elaborated algorithm to real proteomic datasets of low and high resolution. PMID:26230717

Population Pharmacokinetics of Ceftizoxime Administered by Continuous Infusion in Clinically Ill Adult Patients

PubMed Central

Facca, Bryan; Frame, Bill; Triesenberg, Steve

1998-01-01

Ceftizoxime is a widely used beta-lactam antimicrobial agent, but pharmacokinetic data for use with clinically ill patients are lacking. We studied the population pharmacokinetics of ceftizoxime in 72 clinically ill patients at a community-based, university-affiliated hospital. A population pharmacokinetic model for ceftizoxime was created by using a prospective observational design. Ceftizoxime was administered by continuous infusion to treat patients with proven or suspected bacterial infections. While the patients were receiving infusions of ceftizoxime, serum samples were collected for pharmacokinetic analysis with the nonlinear mixed-effect modeling program NONMEM. In addition to clearance and volume of distribution, various comorbidities were examined for their influence on the kinetics. All 72 subjects completed the study, and 114 serum samples were collected. Several demographic and comorbidity variables, namely, age, weight, serum creatinine levels, congestive heart failure, and long-term ventilator dependency, had a significant impact on the estimate for ceftizoxime clearance. A mixture model, or two populations for estimation of ceftizoxime clearance, was discovered. One population presented with an additive clearance component of 1.6 liters per h. In addition, a maximizer function for serum creatinine levels was found. In summary, two models for ceftizoxime clearance, mixture and nonmixture, were found and are presented. Clearance for ceftizoxime can be estimated with commonly available clinical information and the models presented. From the clearance estimates, the dose of ceftizoxime to maintain the desired concentration in serum can be determined. Work is needed to validate the model for drug clearance and to evaluate its predictive performance. PMID:9661021

Identifiability in N-mixture models: a large-scale screening test with bird data.

PubMed

Kéry, Marc

2018-02-01

Binomial N-mixture models have proven very useful in ecology, conservation, and monitoring: they allow estimation and modeling of abundance separately from detection probability using simple counts. Recently, doubts about parameter identifiability have been voiced. I conducted a large-scale screening test with 137 bird data sets from 2,037 sites. I found virtually no identifiability problems for Poisson and zero-inflated Poisson (ZIP) binomial N-mixture models, but negative-binomial (NB) models had problems in 25% of all data sets. The corresponding multinomial N-mixture models had no problems. Parameter estimates under Poisson and ZIP binomial and multinomial N-mixture models were extremely similar. Identifiability problems became a little more frequent with smaller sample sizes (267 and 50 sites), but were unaffected by whether the models did or did not include covariates. Hence, binomial N-mixture model parameters with Poisson and ZIP mixtures typically appeared identifiable. In contrast, NB mixtures were often unidentifiable, which is worrying since these were often selected by Akaike's information criterion. Identifiability of binomial N-mixture models should always be checked. If problems are found, simpler models, integrated models that combine different observation models or the use of external information via informative priors or penalized likelihoods, may help. © 2017 by the Ecological Society of America.

Modeling abundance using multinomial N-mixture models

USGS Publications Warehouse

Royle, Andy

2016-01-01

Multinomial N-mixture models are a generalization of the binomial N-mixture models described in Chapter 6 to allow for more complex and informative sampling protocols beyond simple counts. Many commonly used protocols such as multiple observer sampling, removal sampling, and capture-recapture produce a multivariate count frequency that has a multinomial distribution and for which multinomial N-mixture models can be developed. Such protocols typically result in more precise estimates than binomial mixture models because they provide direct information about parameters of the observation process. We demonstrate the analysis of these models in BUGS using several distinct formulations that afford great flexibility in the types of models that can be developed, and we demonstrate likelihood analysis using the unmarked package. Spatially stratified capture-recapture models are one class of models that fall into the multinomial N-mixture framework, and we discuss analysis of stratified versions of classical models such as model Mb, Mh and other classes of models that are only possible to describe within the multinomial N-mixture framework.

10 CFR 503.9 - Use of mixtures-general requirement for certain permanent exemptions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... exemptions. 503.9 Section 503.9 Energy DEPARTMENT OF ENERGY (CONTINUED) ALTERNATE FUELS NEW FACILITIES... and petroleum and an alternate fuel for which an exemption under 10 CFR 503.38 (Fuel mixtures) would... substitute mixture, such other alternate fuels as OFE and the petitioner agree are reasonable to petitioner's...

Continuous Wavelet Transform, a powerful alternative to Derivative Spectrophotometry in analysis of binary and ternary mixtures: A comparative study.

PubMed

Elzanfaly, Eman S; Hassan, Said A; Salem, Maissa Y; El-Zeany, Badr A

2015-12-05

A comparative study was established between two signal processing techniques showing the theoretical algorithm for each method and making a comparison between them to indicate the advantages and limitations. The methods under study are Numerical Differentiation (ND) and Continuous Wavelet Transform (CWT). These methods were studied as spectrophotometric resolution tools for simultaneous analysis of binary and ternary mixtures. To present the comparison, the two methods were applied for the resolution of Bisoprolol (BIS) and Hydrochlorothiazide (HCT) in their binary mixture and for the analysis of Amlodipine (AML), Aliskiren (ALI) and Hydrochlorothiazide (HCT) as an example for ternary mixtures. By comparing the results in laboratory prepared mixtures, it was proven that CWT technique is more efficient and advantageous in analysis of mixtures with severe overlapped spectra than ND. The CWT was applied for quantitative determination of the drugs in their pharmaceutical formulations and validated according to the ICH guidelines where accuracy, precision, repeatability and robustness were found to be within the acceptable limit. Copyright © 2015 Elsevier B.V. All rights reserved.

Continuous Flow Aerobic Alcohol Oxidation Reactions Using a Heterogeneous Ru(OH)x/Al2O3 Catalyst

PubMed Central

2015-01-01

Ru(OH)x/Al2O3 is among the more versatile catalysts for aerobic alcohol oxidation and dehydrogenation of nitrogen heterocycles. Here, we describe the translation of batch reactions to a continuous-flow method that enables high steady-state conversion and single-pass yields in the oxidation of benzylic alcohols and dehydrogenation of indoline. A dilute source of O2 (8% in N2) was used to ensure that the reaction mixture, which employs toluene as the solvent, is nonflammable throughout the process. A packed bed reactor was operated isothermally in an up-flow orientation, allowing good liquid–solid contact. Deactivation of the catalyst during the reaction was modeled empirically, and this model was used to achieve high conversion and yield during extended operation in the aerobic oxidation of 2-thiophene methanol (99+% continuous yield over 72 h). PMID:25620869

Shear rate analysis of water dynamic in the continuous stirred tank

NASA Astrophysics Data System (ADS)

Tulus; Mardiningsih; Sawaluddin; Sitompul, O. S.; Ihsan, A. K. A. M.

2018-02-01

Analysis of mixture in a continuous stirred tank reactor (CSTR) is an important part in some process of biogas production. This paper is a preliminary study of fluid dynamic phenomenon in a continuous stirred tank numerically. The tank is designed in the form of cylindrical tank equipped with a stirrer. In this study, it is considered that the tank is filled with water. Stirring is done with a stirring speed of 10rpm, 15rpm, 20rpm, and 25rpm. Mathematical modeling of stirred tank is derived. The model is calculated by using the finite element method that are calculated using CFD software. The result shows that the shear rate is high on the front end portion of the stirrer. The maximum shear rate tend to a stable behaviour after the stirring time of 2 second. The relation between the speed and the maximum shear rate is in the form of linear equation.

Concentration addition and independent action model: Which is better in predicting the toxicity for metal mixtures on zebrafish larvae.

PubMed

Gao, Yongfei; Feng, Jianfeng; Kang, Lili; Xu, Xin; Zhu, Lin

2018-01-01

The joint toxicity of chemical mixtures has emerged as a popular topic, particularly on the additive and potential synergistic actions of environmental mixtures. We investigated the 24h toxicity of Cu-Zn, Cu-Cd, and Cu-Pb and 96h toxicity of Cd-Pb binary mixtures on the survival of zebrafish larvae. Joint toxicity was predicted and compared using the concentration addition (CA) and independent action (IA) models with different assumptions in the toxic action mode in toxicodynamic processes through single and binary metal mixture tests. Results showed that the CA and IA models presented varying predictive abilities for different metal combinations. For the Cu-Cd and Cd-Pb mixtures, the CA model simulated the observed survival rates better than the IA model. By contrast, the IA model simulated the observed survival rates better than the CA model for the Cu-Zn and Cu-Pb mixtures. These findings revealed that the toxic action mode may depend on the combinations and concentrations of tested metal mixtures. Statistical analysis of the antagonistic or synergistic interactions indicated that synergistic interactions were observed for the Cu-Cd and Cu-Pb mixtures, non-interactions were observed for the Cd-Pb mixtures, and slight antagonistic interactions for the Cu-Zn mixtures. These results illustrated that the CA and IA models are consistent in specifying the interaction patterns of binary metal mixtures. Copyright © 2017 Elsevier B.V. All rights reserved.

Concentration Addition, Independent Action and Generalized Concentration Addition Models for Mixture Effect Prediction of Sex Hormone Synthesis In Vitro

PubMed Central

Hadrup, Niels; Taxvig, Camilla; Pedersen, Mikael; Nellemann, Christine; Hass, Ulla; Vinggaard, Anne Marie

2013-01-01

Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals. PMID:23990906

Implementation of Ultrasonic Sensing for High Resolution Measurement of Binary Gas Mixture Fractions

PubMed Central

Bates, Richard; Battistin, Michele; Berry, Stephane; Bitadze, Alexander; Bonneau, Pierre; Bousson, Nicolas; Boyd, George; Bozza, Gennaro; Crespo-Lopez, Olivier; Riva, Enrico Da; Degeorge, Cyril; Deterre, Cecile; DiGirolamo, Beniamino; Doubek, Martin; Favre, Gilles; Godlewski, Jan; Hallewell, Gregory; Hasib, Ahmed; Katunin, Sergey; Langevin, Nicolas; Lombard, Didier; Mathieu, Michel; McMahon, Stephen; Nagai, Koichi; Pearson, Benjamin; Robinson, David; Rossi, Cecilia; Rozanov, Alexandre; Strauss, Michael; Vitek, Michal; Vacek, Vaclav; Zwalinski, Lukasz

2014-01-01

We describe an ultrasonic instrument for continuous real-time analysis of the fractional mixture of a binary gas system. The instrument is particularly well suited to measurement of leaks of a high molecular weight gas into a system that is nominally composed of a single gas. Sensitivity < 5 × 10−5 is demonstrated to leaks of octaflouropropane (C3F8) coolant into nitrogen during a long duration (18 month) continuous study. The sensitivity of the described measurement system is shown to depend on the difference in molecular masses of the two gases in the mixture. The impact of temperature and pressure variances on the accuracy of the measurement is analysed. Practical considerations for the implementation and deployment of long term, in situ ultrasonic leak detection systems are also described. Although development of the described systems was motivated by the requirements of an evaporative fluorocarbon cooling system, the instrument is applicable to the detection of leaks of many other gases and to processes requiring continuous knowledge of particular binary gas mixture fractions. PMID:24961217

Detecting Mixtures from Structural Model Differences Using Latent Variable Mixture Modeling: A Comparison of Relative Model Fit Statistics

ERIC Educational Resources Information Center

Henson, James M.; Reise, Steven P.; Kim, Kevin H.

2007-01-01

The accuracy of structural model parameter estimates in latent variable mixture modeling was explored with a 3 (sample size) [times] 3 (exogenous latent mean difference) [times] 3 (endogenous latent mean difference) [times] 3 (correlation between factors) [times] 3 (mixture proportions) factorial design. In addition, the efficacy of several…

Maximum likelihood estimation of finite mixture model for economic data

NASA Astrophysics Data System (ADS)

Phoong, Seuk-Yen; Ismail, Mohd Tahir

2014-06-01

Finite mixture model is a mixture model with finite-dimension. This models are provides a natural representation of heterogeneity in a finite number of latent classes. In addition, finite mixture models also known as latent class models or unsupervised learning models. Recently, maximum likelihood estimation fitted finite mixture models has greatly drawn statistician's attention. The main reason is because maximum likelihood estimation is a powerful statistical method which provides consistent findings as the sample sizes increases to infinity. Thus, the application of maximum likelihood estimation is used to fit finite mixture model in the present paper in order to explore the relationship between nonlinear economic data. In this paper, a two-component normal mixture model is fitted by maximum likelihood estimation in order to investigate the relationship among stock market price and rubber price for sampled countries. Results described that there is a negative effect among rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia.

Charge-based separation of particles and cells with similar sizes via the wall-induced electrical lift.

PubMed

Thomas, Cory; Lu, Xinyu; Todd, Andrew; Raval, Yash; Tzeng, Tzuen-Rong; Song, Yongxin; Wang, Junsheng; Li, Dongqing; Xuan, Xiangchun

2017-01-01

The separation of particles and cells in a uniform mixture has been extensively studied as a necessity in many chemical and biomedical engineering and research fields. This work demonstrates a continuous charge-based separation of fluorescent and plain spherical polystyrene particles with comparable sizes in a ψ-shaped microchannel via the wall-induced electrical lift. The effects of both the direct current electric field in the main-branch and the electric field ratio in between the inlet branches for sheath fluid and particle mixture are investigated on this electrokinetic particle separation. A Lagrangian tracking method based theoretical model is also developed to understand the particle transport in the microchannel and simulate the parametric effects on particle separation. Moreover, the demonstrated charge-based separation is applied to a mixture of yeast cells and polystyrene particles with similar sizes. Good separation efficiency and purity are achieved for both the cells and the particles. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Determination of reaction rates and activation energy in aerobic composting processes for yard waste.

PubMed

Uma, R N; Manjula, G; Meenambal, T

2007-04-01

The reaction rates and activation energy in aerobic composting processes for yard waste were determined using specifically designed reactors. Different mixture ratios were fixed before the commencement of the process. The C/N ratio was found to be optimum for a mixture ratio of 1:6 containing one part of coir pith to six parts of other waste which included yard waste, yeast sludge, poultry yard waste and decomposing culture (Pleurotosis). The path of stabilization of the wastes was continuously monitored by observing various parameters such as temperature, pH, Electrical Conductivity, C.O.D, VS at regular time intervals. Kinetic analysis was done to determine the reaction rates and activation energy for the optimum mixture ratio under forced aeration condition. The results of the analysis clearly indicated that the temperature dependence of the reaction rates followed the Arrhenius equation. The temperature coefficients were also determined. The degradation of the organic fraction of the yard waste could be predicted using first order reaction model.

Meta-Analysis of a Continuous Outcome Combining Individual Patient Data and Aggregate Data: A Method Based on Simulated Individual Patient Data

ERIC Educational Resources Information Center

Yamaguchi, Yusuke; Sakamoto, Wataru; Goto, Masashi; Staessen, Jan A.; Wang, Jiguang; Gueyffier, Francois; Riley, Richard D.

2014-01-01

When some trials provide individual patient data (IPD) and the others provide only aggregate data (AD), meta-analysis methods for combining IPD and AD are required. We propose a method that reconstructs the missing IPD for AD trials by a Bayesian sampling procedure and then applies an IPD meta-analysis model to the mixture of simulated IPD and…

Scalable clustering algorithms for continuous environmental flow cytometry.

PubMed

Hyrkas, Jeremy; Clayton, Sophie; Ribalet, Francois; Halperin, Daniel; Armbrust, E Virginia; Howe, Bill

2016-02-01

Recent technological innovations in flow cytometry now allow oceanographers to collect high-frequency flow cytometry data from particles in aquatic environments on a scale far surpassing conventional flow cytometers. The SeaFlow cytometer continuously profiles microbial phytoplankton populations across thousands of kilometers of the surface ocean. The data streams produced by instruments such as SeaFlow challenge the traditional sample-by-sample approach in cytometric analysis and highlight the need for scalable clustering algorithms to extract population information from these large-scale, high-frequency flow cytometers. We explore how available algorithms commonly used for medical applications perform at classification of such a large-scale, environmental flow cytometry data. We apply large-scale Gaussian mixture models to massive datasets using Hadoop. This approach outperforms current state-of-the-art cytometry classification algorithms in accuracy and can be coupled with manual or automatic partitioning of data into homogeneous sections for further classification gains. We propose the Gaussian mixture model with partitioning approach for classification of large-scale, high-frequency flow cytometry data. Source code available for download at https://github.com/jhyrkas/seaflow_cluster, implemented in Java for use with Hadoop. hyrkas@cs.washington.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Optimizing surface finishing processes through the use of novel solvents and systems

NASA Astrophysics Data System (ADS)

Quillen, M.; Holbrook, P.; Moore, J.

2007-03-01

As the semiconductor industry continues to implement the ITRS (International Technology Roadmap for Semiconductors) node targets that go beyond 45nm [1], the need for improved cleanliness between repeated process steps continues to grow. Wafer cleaning challenges cover many applications such as Cu/low-K integration, where trade-offs must be made between dielectric damage and residue by plasma etching and CMP or moisture uptake by aqueous cleaning products. [2-5] Some surface sensitive processes use the Marangoni tool design [6] where a conventional solvent such as IPA (isopropanol), combines with water to provide improved physical properties such as reduced contact angle and surface tension. This paper introduces the use of alternative solvents and their mixtures compared to pure IPA in removing ionics, moisture, and particles using immersion bench-chemistry models of various processes. A novel Eastman proprietary solvent, Eastman methyl acetate is observed to provide improvement in ionic, moisture capture, and particle removal, as compared to conventional IPA. [7] These benefits may be improved relative to pure IPA, simply by the addition of various additives. Some physical properties of the mixtures were found to be relatively unchanged even as measured performance improved. This report presents our attempts to cite and optimize these benefits through the use of laboratory models.

Predicting herbicide mixture effects on multiple algal species using mixture toxicity models.

PubMed

Nagai, Takashi

2017-10-01

The validity of the application of mixture toxicity models, concentration addition and independent action, to a species sensitivity distribution (SSD) for calculation of a multisubstance potentially affected fraction was examined in laboratory experiments. Toxicity assays of herbicide mixtures using 5 species of periphytic algae were conducted. Two mixture experiments were designed: a mixture of 5 herbicides with similar modes of action and a mixture of 5 herbicides with dissimilar modes of action, corresponding to the assumptions of the concentration addition and independent action models, respectively. Experimentally obtained mixture effects on 5 algal species were converted to the fraction of affected (>50% effect on growth rate) species. The predictive ability of the concentration addition and independent action models with direct application to SSD depended on the mode of action of chemicals. That is, prediction was better for the concentration addition model than the independent action model for the mixture of herbicides with similar modes of action. In contrast, prediction was better for the independent action model than the concentration addition model for the mixture of herbicides with dissimilar modes of action. Thus, the concentration addition and independent action models could be applied to SSD in the same manner as for a single-species effect. The present study to validate the application of the concentration addition and independent action models to SSD supports the usefulness of the multisubstance potentially affected fraction as the index of ecological risk. Environ Toxicol Chem 2017;36:2624-2630. © 2017 SETAC. © 2017 SETAC.

Mapping of quantitative trait loci using the skew-normal distribution.

PubMed

Fernandes, Elisabete; Pacheco, António; Penha-Gonçalves, Carlos

2007-11-01

In standard interval mapping (IM) of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. When this assumption of normality is violated, the most commonly adopted strategy is to use the previous model after data transformation. However, an appropriate transformation may not exist or may be difficult to find. Also this approach can raise interpretation issues. An interesting alternative is to consider a skew-normal mixture model in standard IM, and the resulting method is here denoted as skew-normal IM. This flexible model that includes the usual symmetric normal distribution as a special case is important, allowing continuous variation from normality to non-normality. In this paper we briefly introduce the main peculiarities of the skew-normal distribution. The maximum likelihood estimates of parameters of the skew-normal distribution are obtained by the expectation-maximization (EM) algorithm. The proposed model is illustrated with real data from an intercross experiment that shows a significant departure from the normality assumption. The performance of the skew-normal IM is assessed via stochastic simulation. The results indicate that the skew-normal IM has higher power for QTL detection and better precision of QTL location as compared to standard IM and nonparametric IM.

Monte Carlo simulation of two-component bilayers: DMPC/DSPC mixtures.

PubMed Central

Sugár, I P; Thompson, T E; Biltonen, R L

1999-01-01

In this paper, we describe a relatively simple lattice model of a two-component, two-state phospholipid bilayer. Application of Monte Carlo methods to this model permits simulation of the observed excess heat capacity versus temperature curves of dimyristoylphosphatidylcholine (DMPC)/distearoylphosphatidylcholine (DSPC) mixtures as well as the lateral distributions of the components and properties related to these distributions. The analysis of the bilayer energy distribution functions reveals that the gel-fluid transition is a continuous transition for DMPC, DSPC, and all DMPC/DSPC mixtures. A comparison of the thermodynamic properties of DMPC/DSPC mixtures with the configurational properties shows that the temperatures characteristics of the configurational properties correlate well with the maxima in the excess heat capacity curves rather than with the onset and completion temperatures of the gel-fluid transition. In the gel-fluid coexistence region, we also found excellent agreement between the threshold temperatures at different system compositions detected in fluorescence recovery after photobleaching experiments and the temperatures at which the percolation probability of the gel clusters is 0.36. At every composition, the calculated mole fraction of gel state molecules at the fluorescence recovery after photobleaching threshold is 0.34 and, at the percolation threshold of gel clusters, it is 0.24. The percolation threshold mole fraction of gel or fluid lipid depends on the packing geometry of the molecules and the interchain interactions. However, it is independent of temperature, system composition, and state of the percolating cluster. PMID:10096905

10 CFR 503.38 - Permanent exemption for certain fuel mixtures containing natural gas or petroleum.

Code of Federal Regulations, 2010 CFR

2010-01-01

... natural gas or petroleum. 503.38 Section 503.38 Energy DEPARTMENT OF ENERGY (CONTINUED) ALTERNATE FUELS... mixtures containing natural gas or petroleum. (a) Eligibility. Section 212(d) of the Act provides for a... proposes to use a mixture of natural gas or petroleum and an alternate fuel as a primary energy source; (2...

Coordinated Hard Sphere Mixture (CHaSM): A simplified model for oxide and silicate melts at mantle pressures and temperatures

NASA Astrophysics Data System (ADS)

Wolf, Aaron S.; Asimow, Paul D.; Stevenson, David J.

2015-08-01

We develop a new model to understand and predict the behavior of oxide and silicate melts at extreme temperatures and pressures, including deep mantle conditions like those in the early Earth magma ocean. The Coordinated Hard Sphere Mixture (CHaSM) is based on an extension of the hard sphere mixture model, accounting for the range of coordination states available to each cation in the liquid. By utilizing approximate analytic expressions for the hard sphere model, this method is capable of predicting complex liquid structure and thermodynamics while remaining computationally efficient, requiring only minutes of calculation time on standard desktop computers. This modeling framework is applied to the MgO system, where model parameters are trained on a collection of crystal polymorphs, producing realistic predictions of coordination evolution and the equation of state of MgO melt over a wide range of pressures and temperatures. We find that the typical coordination number of the Mg cation evolves continuously upward from 5.25 at 0 GPa to 8.5 at 250 GPa. The results produced by CHaSM are evaluated by comparison with predictions from published first-principles molecular dynamics calculations, indicating that CHaSM is accurately capturing the dominant physics controlling the behavior of oxide melts at high pressure. Finally, we present a simple quantitative model to explain the universality of the increasing Grüneisen parameter trend for liquids, which directly reflects their progressive evolution toward more compact solid-like structures upon compression. This general behavior is opposite that of solid materials, and produces steep adiabatic thermal profiles for silicate melts, thus playing a crucial role in magma ocean evolution.

27 CFR 19.297 - Use of materials in production of spirits.

Code of Federal Regulations, 2012 CFR

2012-04-01

... of production procedure. The distillation of nonpotable chemical mixtures as described in § 19.36 will be deemed to be the original and continuous distillation of the spirits in such mixtures and to...

27 CFR 19.297 - Use of materials in production of spirits.

Code of Federal Regulations, 2014 CFR

2014-04-01

... of production procedure. The distillation of nonpotable chemical mixtures as described in § 19.36 will be deemed to be the original and continuous distillation of the spirits in such mixtures and to...

27 CFR 19.297 - Use of materials in production of spirits.

Code of Federal Regulations, 2011 CFR

2011-04-01

... of production procedure. The distillation of nonpotable chemical mixtures as described in § 19.36 will be deemed to be the original and continuous distillation of the spirits in such mixtures and to...

27 CFR 19.297 - Use of materials in production of spirits.

Code of Federal Regulations, 2013 CFR

2013-04-01

... of production procedure. The distillation of nonpotable chemical mixtures as described in § 19.36 will be deemed to be the original and continuous distillation of the spirits in such mixtures and to...

Dual Superlyophobic Copper Foam with Good Durability and Recyclability for High Flux, High Efficiency, and Continuous Oil-Water Separation.

PubMed

Zhou, Wenting; Li, Song; Liu, Yan; Xu, Zhengzheng; Wei, Sufeng; Wang, Guoyong; Lian, Jianshe; Jiang, Qing

2018-03-21

Traditional oil-water separation materials have to own ultrahigh or ultralow surface energy. Thus, they can only be wetted by one of the two, oil or water. Our experiment here demonstrates that the wettability in oil-water mixtures can be tuned by oil and water initially. Hierarchical voids are built on commercial copper foams with the help of hydrothermally synthesized titanium dioxide nanorods. The foams can be easily wetted by both oil and water. The water prewetted foams are superhydrophilic and superoleophobic under oil-water mixtures, meanwhile the oil prewetted foams are superoleophilic and superhydrophobic. In this paper, many kinds of water-oil mixtures were separated by two foams, prewetted by corresponding oil or water, respectively, combining a straight tee in a high flux, high efficiency, and continuous mode. This research indicates that oil-water mixtures can be separated more eco-friendly and at lower cost.

Measurement and Structural Model Class Separation in Mixture CFA: ML/EM versus MCMC

ERIC Educational Resources Information Center

Depaoli, Sarah

2012-01-01

Parameter recovery was assessed within mixture confirmatory factor analysis across multiple estimator conditions under different simulated levels of mixture class separation. Mixture class separation was defined in the measurement model (through factor loadings) and the structural model (through factor variances). Maximum likelihood (ML) via the…

ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.

PubMed

Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J

2014-07-01

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.

A study of finite mixture model: Bayesian approach on financial time series data

NASA Astrophysics Data System (ADS)

Phoong, Seuk-Yen; Ismail, Mohd Tahir

2014-07-01

Recently, statistician have emphasized on the fitting finite mixture model by using Bayesian method. Finite mixture model is a mixture of distributions in modeling a statistical distribution meanwhile Bayesian method is a statistical method that use to fit the mixture model. Bayesian method is being used widely because it has asymptotic properties which provide remarkable result. In addition, Bayesian method also shows consistency characteristic which means the parameter estimates are close to the predictive distributions. In the present paper, the number of components for mixture model is studied by using Bayesian Information Criterion. Identify the number of component is important because it may lead to an invalid result. Later, the Bayesian method is utilized to fit the k-component mixture model in order to explore the relationship between rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia. Lastly, the results showed that there is a negative effect among rubber price and stock market price for all selected countries.

Continuous bio-catalytic conversion of sugar mixture to acetone-butanol-ethanol by immobilized Clostridium acetobutylicum DSM 792.

PubMed

Survase, Shrikant A; van Heiningen, Adriaan; Granström, Tom

2012-03-01

Continuous production of acetone, n-butanol, and ethanol (ABE) was carried out using immobilized cells of Clostridium acetobutylicum DSM 792 using glucose and sugar mixture as a substrate. Among various lignocellulosic materials screened as a support matrix, coconut fibers and wood pulp fibers were found to be promising in batch experiments. With a motive of promoting wood-based bio-refinery concept, wood pulp was used as a cell holding material. Glucose and sugar mixture (glucose, mannose, galactose, arabinose, and xylose) comparable to lignocellulose hydrolysate was used as a substrate for continuous production of ABE. We report the best solvent productivity among wild-type strains using column reactor. The maximum total solvent concentration of 14.32 g L(-1) was obtained at a dilution rate of 0.22 h(-1) with glucose as a substrate compared to 12.64 g L(-1) at 0.5 h(-1) dilution rate with sugar mixture. The maximum solvent productivity (13.66 g L(-1) h(-1)) was obtained at a dilution rate of 1.9 h(-1) with glucose as a substrate whereas solvent productivity (12.14 g L(-1) h(-1)) was obtained at a dilution rate of 1.5 h(-1) with sugar mixture. The immobilized column reactor with wood pulp can become an efficient technology to be integrated with existing pulp mills to convert them into wood-based bio-refineries.

Decoding with limited neural data: a mixture of time-warped trajectory models for directional reaches.

PubMed

Corbett, Elaine A; Perreault, Eric J; Körding, Konrad P

2012-06-01

Neuroprosthetic devices promise to allow paralyzed patients to perform the necessary functions of everyday life. However, to allow patients to use such tools it is necessary to decode their intent from neural signals such as electromyograms (EMGs). Because these signals are noisy, state of the art decoders integrate information over time. One systematic way of doing this is by taking into account the natural evolution of the state of the body--by using a so-called trajectory model. Here we use two insights about movements to enhance our trajectory model: (1) at any given time, there is a small set of likely movement targets, potentially identified by gaze; (2) reaches are produced at varying speeds. We decoded natural reaching movements using EMGs of muscles that might be available from an individual with spinal cord injury. Target estimates found from tracking eye movements were incorporated into the trajectory model, while a mixture model accounted for the inherent uncertainty in these estimates. Warping the trajectory model in time using a continuous estimate of the reach speed enabled accurate decoding of faster reaches. We found that the choice of richer trajectory models, such as those incorporating target or speed, improves decoding particularly when there is a small number of EMGs available.

Accounting for non-independent detection when estimating abundance of organisms with a Bayesian approach

USGS Publications Warehouse

Martin, Julien; Royle, J. Andrew; MacKenzie, Darryl I.; Edwards, Holly H.; Kery, Marc; Gardner, Beth

2011-01-01

Summary 1. Binomial mixture models use repeated count data to estimate abundance. They are becoming increasingly popular because they provide a simple and cost-effective way to account for imperfect detection. However, these models assume that individuals are detected independently of each other. This assumption may often be violated in the field. For instance, manatees (Trichechus manatus latirostris) may surface in turbid water (i.e. become available for detection during aerial surveys) in a correlated manner (i.e. in groups). However, correlated behaviour, affecting the non-independence of individual detections, may also be relevant in other systems (e.g. correlated patterns of singing in birds and amphibians). 2. We extend binomial mixture models to account for correlated behaviour and therefore to account for non-independent detection of individuals. We simulated correlated behaviour using beta-binomial random variables. Our approach can be used to simultaneously estimate abundance, detection probability and a correlation parameter. 3. Fitting binomial mixture models to data that followed a beta-binomial distribution resulted in an overestimation of abundance even for moderate levels of correlation. In contrast, the beta-binomial mixture model performed considerably better in our simulation scenarios. We also present a goodness-of-fit procedure to evaluate the fit of beta-binomial mixture models. 4. We illustrate our approach by fitting both binomial and beta-binomial mixture models to aerial survey data of manatees in Florida. We found that the binomial mixture model did not fit the data, whereas there was no evidence of lack of fit for the beta-binomial mixture model. This example helps illustrate the importance of using simulations and assessing goodness-of-fit when analysing ecological data with N-mixture models. Indeed, both the simulations and the goodness-of-fit procedure highlighted the limitations of the standard binomial mixture model for aerial manatee surveys. 5. Overestimation of abundance by binomial mixture models owing to non-independent detections is problematic for ecological studies, but also for conservation. For example, in the case of endangered species, it could lead to inappropriate management decisions, such as downlisting. These issues will be increasingly relevant as more ecologists apply flexible N-mixture models to ecological data.

A competitive binding model predicts the response of mammalian olfactory receptors to mixtures

NASA Astrophysics Data System (ADS)

Singh, Vijay; Murphy, Nicolle; Mainland, Joel; Balasubramanian, Vijay

Most natural odors are complex mixtures of many odorants, but due to the large number of possible mixtures only a small fraction can be studied experimentally. To get a realistic understanding of the olfactory system we need methods to predict responses to complex mixtures from single odorant responses. Focusing on mammalian olfactory receptors (ORs in mouse and human), we propose a simple biophysical model for odor-receptor interactions where only one odor molecule can bind to a receptor at a time. The resulting competition for occupancy of the receptor accounts for the experimentally observed nonlinear mixture responses. We first fit a dose-response relationship to individual odor responses and then use those parameters in a competitive binding model to predict mixture responses. With no additional parameters, the model predicts responses of 15 (of 18 tested) receptors to within 10 - 30 % of the observed values, for mixtures with 2, 3 and 12 odorants chosen from a panel of 30. Extensions of our basic model with odorant interactions lead to additional nonlinearities observed in mixture response like suppression, cooperativity, and overshadowing. Our model provides a systematic framework for characterizing and parameterizing such mixing nonlinearities from mixture response data.

Discontinuous finite volume element discretization for coupled flow-transport problems arising in models of sedimentation

NASA Astrophysics Data System (ADS)

Bürger, Raimund; Kumar, Sarvesh; Ruiz-Baier, Ricardo

2015-10-01

The sedimentation-consolidation and flow processes of a mixture of small particles dispersed in a viscous fluid at low Reynolds numbers can be described by a nonlinear transport equation for the solids concentration coupled with the Stokes problem written in terms of the mixture flow velocity and the pressure field. Here both the viscosity and the forcing term depend on the local solids concentration. A semi-discrete discontinuous finite volume element (DFVE) scheme is proposed for this model. The numerical method is constructed on a baseline finite element family of linear discontinuous elements for the approximation of velocity components and concentration field, whereas the pressure is approximated by piecewise constant elements. The unique solvability of both the nonlinear continuous problem and the semi-discrete DFVE scheme is discussed, and optimal convergence estimates in several spatial norms are derived. Properties of the model and the predicted space accuracy of the proposed formulation are illustrated by detailed numerical examples, including flows under gravity with changing direction, a secondary settling tank in an axisymmetric setting, and batch sedimentation in a tilted cylindrical vessel.

PBDES: TOXICOLOGY UPDATE

EPA Science Inventory

Polybrominated diphenyl ethers (PBDEs) have been major commercial products used as flame retardants. While two of the commercial mixtures, Penta and Octa, have either been withdrawn or banned in Europe and the US respectively, the largest volume mixture, Deca, continues to be wi...

Effective chemotherapy of heterogeneous and drug-resistant early colon cancers by intermittent dose schedules: a computer simulation study.

PubMed

Axelrod, David E; Vedula, Sudeepti; Obaniyi, James

2017-05-01

The effectiveness of cancer chemotherapy is limited by intra-tumor heterogeneity, the emergence of spontaneous and induced drug-resistant mutant subclones, and the maximum dose to which normal tissues can be exposed without adverse side effects. The goal of this project was to determine if intermittent schedules of the maximum dose that allows colon crypt maintenance could overcome these limitations, specifically by eliminating mixtures of drug-resistant mutants from heterogeneous early colon adenomas while maintaining colon crypt function. A computer model of cell dynamics in human colon crypts was calibrated with measurements of human biopsy specimens. The model allowed simulation of continuous and intermittent dose schedules of a cytotoxic chemotherapeutic drug, as well as the drug's effect on the elimination of mutant cells and the maintenance of crypt function. Colon crypts can tolerate a tenfold greater intermittent dose than constant dose. This allows elimination of a mixture of relatively drug-sensitive and drug-resistant mutant subclones from heterogeneous colon crypts. Mutants can be eliminated whether they arise spontaneously or are induced by the cytotoxic drug. An intermittent dose, at the maximum that allows colon crypt maintenance, can be effective in eliminating a heterogeneous mixture of mutant subclones before they fill the crypt and form an adenoma.

Molecular dynamics of acetamide based ionic deep eutectic solvents

NASA Astrophysics Data System (ADS)

Srinivasan, H.; Dubey, P. S.; Sharma, V. K.; Biswas, R.; Mitra, S.; Mukhopadhyay, R.

2018-04-01

Deep eutectic solvents are multi-component mixtures that have freezing point lower than their individual components. Mixture of acetamide+ lithium nitrate in the molar ratio 78:22 and acetamide+ lithium perchlorate in the molar ratio 81:19 are found to form deep eutectic solvents with melting point lower than the room temperature. It is known that the depression in freezing point is due to the hydrogen bond breaking ability of anions in the system. Quasielastic neutron scattering experiments on these systems were carried out to study the dynamics of acetamide molecules which may be influenced by this hydrogen bond breaking phenomena. The motion of acetamide molecules is modeled using jump diffusion mechanism to demonstrate continuous breaking and reforming hydrogen bonds in the solvent. Using the jump diffusion model, it is inferred that the jump lengths of acetamide molecules are better approximated by a Gaussian distribution. The shorter residence time of acetamide in presence of perchlorate ions suggest that the perchlorate ions have a higher hydrogen bond breaking ability compared to nitrate ions.

Estimation of value at risk and conditional value at risk using normal mixture distributions model

NASA Astrophysics Data System (ADS)

Kamaruzzaman, Zetty Ain; Isa, Zaidi

2013-04-01

Normal mixture distributions model has been successfully applied in financial time series analysis. In this paper, we estimate the return distribution, value at risk (VaR) and conditional value at risk (CVaR) for monthly and weekly rates of returns for FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) from July 1990 until July 2010 using the two component univariate normal mixture distributions model. First, we present the application of normal mixture distributions model in empirical finance where we fit our real data. Second, we present the application of normal mixture distributions model in risk analysis where we apply the normal mixture distributions model to evaluate the value at risk (VaR) and conditional value at risk (CVaR) with model validation for both risk measures. The empirical results provide evidence that using the two components normal mixture distributions model can fit the data well and can perform better in estimating value at risk (VaR) and conditional value at risk (CVaR) where it can capture the stylized facts of non-normality and leptokurtosis in returns distribution.

Reduced chemical kinetic model of detonation combustion of one- and multi-fuel gaseous mixtures with air

NASA Astrophysics Data System (ADS)

Fomin, P. A.

2018-03-01

Two-step approximate models of chemical kinetics of detonation combustion of (i) one hydrocarbon fuel CnHm (for example, methane, propane, cyclohexane etc.) and (ii) multi-fuel gaseous mixtures (∑aiCniHmi) (for example, mixture of methane and propane, synthesis gas, benzene and kerosene) are presented for the first time. The models can be used for any stoichiometry, including fuel/fuels-rich mixtures, when reaction products contain molecules of carbon. Owing to the simplicity and high accuracy, the models can be used in multi-dimensional numerical calculations of detonation waves in corresponding gaseous mixtures. The models are in consistent with the second law of thermodynamics and Le Chatelier's principle. Constants of the models have a clear physical meaning. The models can be used for calculation thermodynamic parameters of the mixture in a state of chemical equilibrium.

Continuous flow immobilized enzyme reactor-tandem mass spectrometry for screening of AChE inhibitors in complex mixtures.

PubMed

Forsberg, Erica M; Green, James R A; Brennan, John D

2011-07-01

A method is described for identifying bioactive compounds in complex mixtures based on the use of capillary-scale monolithic enzyme-reactor columns for rapid screening of enzyme activity. A two-channel nanoLC system was used to continuously infuse substrate coupled with automated injections of substrate/small molecule mixtures, optionally containing the chromogenic Ellman reagent, through sol-gel derived acetylcholinesterase (AChE) doped monolithic columns. This is the first report of AChE encapsulated in monolithic silica for use as an immobilized enzyme reactor (IMER), and the first use of such IMERs for mixture screening. AChE IMER columns were optimized to allow rapid functional screening of compound mixtures based on changes in the product absorbance or the ratio of mass spectrometric peaks for product and substrate ions in the eluent. The assay had robust performance and produced a Z' factor of 0.77 in the presence of 2% (v/v) DMSO. A series of 52 mixtures consisting of 1040 compounds from the Canadian Compound Collection of bioactives was screened and two known inhibitors, physostigmine and 9-aminoacridine, were identified from active mixtures by manual deconvolution. The activity of the compounds was confirmed using the enzyme reactor format, which allowed determination of both IC(50) and K(I) values. Screening results were found to correlate well with a recently published fluorescence-based microarray screening assay for AChE inhibitors.

ODE Constrained Mixture Modelling: A Method for Unraveling Subpopulation Structures and Dynamics

PubMed Central

Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J.

2014-01-01

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity. PMID:24992156

Applicability study of classical and contemporary models for effective complex permittivity of metal powders.

PubMed

Kiley, Erin M; Yakovlev, Vadim V; Ishizaki, Kotaro; Vaucher, Sebastien

2012-01-01

Microwave thermal processing of metal powders has recently been a topic of a substantial interest; however, experimental data on the physical properties of mixtures involving metal particles are often unavailable. In this paper, we perform a systematic analysis of classical and contemporary models of complex permittivity of mixtures and discuss the use of these models for determining effective permittivity of dielectric matrices with metal inclusions. Results from various mixture and core-shell mixture models are compared to experimental data for a titanium/stearic acid mixture and a boron nitride/graphite mixture (both obtained through the original measurements), and for a tungsten/Teflon mixture (from literature). We find that for certain experiments, the average error in determining the effective complex permittivity using Lichtenecker's, Maxwell Garnett's, Bruggeman's, Buchelnikov's, and Ignatenko's models is about 10%. This suggests that, for multiphysics computer models describing the processing of metal powder in the full temperature range, input data on effective complex permittivity obtained from direct measurement has, up to now, no substitute.

Modeling and analysis of personal exposures to VOC mixtures using copulas

PubMed Central

Su, Feng-Chiao; Mukherjee, Bhramar; Batterman, Stuart

2014-01-01

Environmental exposures typically involve mixtures of pollutants, which must be understood to evaluate cumulative risks, that is, the likelihood of adverse health effects arising from two or more chemicals. This study uses several powerful techniques to characterize dependency structures of mixture components in personal exposure measurements of volatile organic compounds (VOCs) with aims of advancing the understanding of environmental mixtures, improving the ability to model mixture components in a statistically valid manner, and demonstrating broadly applicable techniques. We first describe characteristics of mixtures and introduce several terms, including the mixture fraction which represents a mixture component's share of the total concentration of the mixture. Next, using VOC exposure data collected in the Relationship of Indoor Outdoor and Personal Air (RIOPA) study, mixtures are identified using positive matrix factorization (PMF) and by toxicological mode of action. Dependency structures of mixture components are examined using mixture fractions and modeled using copulas, which address dependencies of multiple variables across the entire distribution. Five candidate copulas (Gaussian, t, Gumbel, Clayton, and Frank) are evaluated, and the performance of fitted models was evaluated using simulation and mixture fractions. Cumulative cancer risks are calculated for mixtures, and results from copulas and multivariate lognormal models are compared to risks calculated using the observed data. Results obtained using the RIOPA dataset showed four VOC mixtures, representing gasoline vapor, vehicle exhaust, chlorinated solvents and disinfection by-products, and cleaning products and odorants. Often, a single compound dominated the mixture, however, mixture fractions were generally heterogeneous in that the VOC composition of the mixture changed with concentration. Three mixtures were identified by mode of action, representing VOCs associated with hematopoietic, liver and renal tumors. Estimated lifetime cumulative cancer risks exceeded 10−3 for about 10% of RIOPA participants. Factors affecting the likelihood of high concentration mixtures included city, participant ethnicity, and house air exchange rates. The dependency structures of the VOC mixtures fitted Gumbel (two mixtures) and t (four mixtures) copulas, types that emphasize tail dependencies. Significantly, the copulas reproduced both risk predictions and exposure fractions with a high degree of accuracy, and performed better than multivariate lognormal distributions. Copulas may be the method of choice for VOC mixtures, particularly for the highest exposures or extreme events, cases that poorly fit lognormal distributions and that represent the greatest risks. PMID:24333991

33 CFR 155.330 - Oily mixture (bilge slops)/fuel oil tank ballast water discharges on U.S. non-oceangoing ships.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) POLLUTION OIL OR HAZARDOUS MATERIAL POLLUTION PREVENTION REGULATIONS FOR VESSELS Vessel Equipment § 155.330 Oily mixture (bilge slops...

Asphalt mixture cold temperature performance using the Bending Beam Rheometer (BBR).

DOT National Transportation Integrated Search

2013-03-01

The use of recycled materials providing substitution of virgin binder in asphalt mixtures : continues to increase. The current level of funding for highway construction is : significantly less than 3 years ago and the level of competition between bid...

RB Particle Filter Time Synchronization Algorithm Based on the DPM Model.

PubMed

Guo, Chunsheng; Shen, Jia; Sun, Yao; Ying, Na

2015-09-03

Time synchronization is essential for node localization, target tracking, data fusion, and various other Wireless Sensor Network (WSN) applications. To improve the estimation accuracy of continuous clock offset and skew of mobile nodes in WSNs, we propose a novel time synchronization algorithm, the Rao-Blackwellised (RB) particle filter time synchronization algorithm based on the Dirichlet process mixture (DPM) model. In a state-space equation with a linear substructure, state variables are divided into linear and non-linear variables by the RB particle filter algorithm. These two variables can be estimated using Kalman filter and particle filter, respectively, which improves the computational efficiency more so than if only the particle filter was used. In addition, the DPM model is used to describe the distribution of non-deterministic delays and to automatically adjust the number of Gaussian mixture model components based on the observational data. This improves the estimation accuracy of clock offset and skew, which allows achieving the time synchronization. The time synchronization performance of this algorithm is also validated by computer simulations and experimental measurements. The results show that the proposed algorithm has a higher time synchronization precision than traditional time synchronization algorithms.

A varying-coefficient method for analyzing longitudinal clinical trials data with nonignorable dropout

PubMed Central

Forster, Jeri E.; MaWhinney, Samantha; Ball, Erika L.; Fairclough, Diane

2011-01-01

Dropout is common in longitudinal clinical trials and when the probability of dropout depends on unobserved outcomes even after conditioning on available data, it is considered missing not at random and therefore nonignorable. To address this problem, mixture models can be used to account for the relationship between a longitudinal outcome and dropout. We propose a Natural Spline Varying-coefficient mixture model (NSV), which is a straightforward extension of the parametric Conditional Linear Model (CLM). We assume that the outcome follows a varying-coefficient model conditional on a continuous dropout distribution. Natural cubic B-splines are used to allow the regression coefficients to semiparametrically depend on dropout and inference is therefore more robust. Additionally, this method is computationally stable and relatively simple to implement. We conduct simulation studies to evaluate performance and compare methodologies in settings where the longitudinal trajectories are linear and dropout time is observed for all individuals. Performance is assessed under conditions where model assumptions are both met and violated. In addition, we compare the NSV to the CLM and a standard random-effects model using an HIV/AIDS clinical trial with probable nonignorable dropout. The simulation studies suggest that the NSV is an improvement over the CLM when dropout has a nonlinear dependence on the outcome. PMID:22101223

Method for simulating paint mixing on computer monitors

NASA Astrophysics Data System (ADS)

Carabott, Ferdinand; Lewis, Garth; Piehl, Simon

2002-06-01

Computer programs like Adobe Photoshop can generate a mixture of two 'computer' colors by using the Gradient control. However, the resulting colors diverge from the equivalent paint mixtures in both hue and value. This study examines why programs like Photoshop are unable to simulate paint or pigment mixtures, and offers a solution using Photoshops existing tools. The article discusses how a library of colors, simulating paint mixtures, is created from 13 artists' colors. The mixtures can be imported into Photoshop as a color swatch palette of 1248 colors and as 78 continuous or stepped gradient files, all accessed in a new software package, Chromafile.

Estimation and Model Selection for Finite Mixtures of Latent Interaction Models

ERIC Educational Resources Information Center

Hsu, Jui-Chen

2011-01-01

Latent interaction models and mixture models have received considerable attention in social science research recently, but little is known about how to handle if unobserved population heterogeneity exists in the endogenous latent variables of the nonlinear structural equation models. The current study estimates a mixture of latent interaction…

Scale Mixture Models with Applications to Bayesian Inference

NASA Astrophysics Data System (ADS)

Qin, Zhaohui S.; Damien, Paul; Walker, Stephen

2003-11-01

Scale mixtures of uniform distributions are used to model non-normal data in time series and econometrics in a Bayesian framework. Heteroscedastic and skewed data models are also tackled using scale mixture of uniform distributions.

Characterization of Mixtures. Part 2: QSPR Models for Prediction of Excess Molar Volume and Liquid Density Using Neural Networks.

PubMed

Ajmani, Subhash; Rogers, Stephen C; Barley, Mark H; Burgess, Andrew N; Livingstone, David J

2010-09-17

In our earlier work, we have demonstrated that it is possible to characterize binary mixtures using single component descriptors by applying various mixing rules. We also showed that these methods were successful in building predictive QSPR models to study various mixture properties of interest. Here in, we developed a QSPR model of an excess thermodynamic property of binary mixtures i.e. excess molar volume (V(E) ). In the present study, we use a set of mixture descriptors which we earlier designed to specifically account for intermolecular interactions between the components of a mixture and applied successfully to the prediction of infinite-dilution activity coefficients using neural networks (part 1 of this series). We obtain a significant QSPR model for the prediction of excess molar volume (V(E) ) using consensus neural networks and five mixture descriptors. We find that hydrogen bond and thermodynamic descriptors are the most important in determining excess molar volume (V(E) ), which is in line with the theory of intermolecular forces governing excess mixture properties. The results also suggest that the mixture descriptors utilized herein may be sufficient to model a wide variety of properties of binary and possibly even more complex mixtures. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of reversible jump Markov Chain Monte Carlo algorithm in the Bayesian mixture modeling for microarray data in Indonesia

NASA Astrophysics Data System (ADS)

Astuti, Ani Budi; Iriawan, Nur; Irhamah, Kuswanto, Heri

2017-12-01

In the Bayesian mixture modeling requires stages the identification number of the most appropriate mixture components thus obtained mixture models fit the data through data driven concept. Reversible Jump Markov Chain Monte Carlo (RJMCMC) is a combination of the reversible jump (RJ) concept and the Markov Chain Monte Carlo (MCMC) concept used by some researchers to solve the problem of identifying the number of mixture components which are not known with certainty number. In its application, RJMCMC using the concept of the birth/death and the split-merge with six types of movement, that are w updating, θ updating, z updating, hyperparameter β updating, split-merge for components and birth/death from blank components. The development of the RJMCMC algorithm needs to be done according to the observed case. The purpose of this study is to know the performance of RJMCMC algorithm development in identifying the number of mixture components which are not known with certainty number in the Bayesian mixture modeling for microarray data in Indonesia. The results of this study represent that the concept RJMCMC algorithm development able to properly identify the number of mixture components in the Bayesian normal mixture model wherein the component mixture in the case of microarray data in Indonesia is not known for certain number.

Aquatic exposures of chemical mixtures in urban environments: Approaches to impact assessment.

PubMed

de Zwart, Dick; Adams, William; Galay Burgos, Malyka; Hollender, Juliane; Junghans, Marion; Merrington, Graham; Muir, Derek; Parkerton, Thomas; De Schamphelaere, Karel A C; Whale, Graham; Williams, Richard

2018-03-01

Urban regions of the world are expanding rapidly, placing additional stress on water resources. Urban water bodies serve many purposes, from washing and sources of drinking water to transport and conduits for storm drainage and effluent discharge. These water bodies receive chemical emissions arising from either single or multiple point sources, diffuse sources which can be continuous, intermittent, or seasonal. Thus, aquatic organisms in these water bodies are exposed to temporally and compositionally variable mixtures. We have delineated source-specific signatures of these mixtures for diffuse urban runoff and urban point source exposure scenarios to support risk assessment and management of these mixtures. The first step in a tiered approach to assessing chemical exposure has been developed based on the event mean concentration concept, with chemical concentrations in runoff defined by volumes of water leaving each surface and the chemical exposure mixture profiles for different urban scenarios. Although generalizations can be made about the chemical composition of urban sources and event mean exposure predictions for initial prioritization, such modeling needs to be complemented with biological monitoring data. It is highly unlikely that the current paradigm of routine regulatory chemical monitoring alone will provide a realistic appraisal of urban aquatic chemical mixture exposures. Future consideration is also needed of the role of nonchemical stressors in such highly modified urban water bodies. Environ Toxicol Chem 2018;37:703-714. © 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. © 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

QSAR prediction of additive and non-additive mixture toxicities of antibiotics and pesticide.

PubMed

Qin, Li-Tang; Chen, Yu-Han; Zhang, Xin; Mo, Ling-Yun; Zeng, Hong-Hu; Liang, Yan-Peng

2018-05-01

Antibiotics and pesticides may exist as a mixture in real environment. The combined effect of mixture can either be additive or non-additive (synergism and antagonism). However, no effective predictive approach exists on predicting the synergistic and antagonistic toxicities of mixtures. In this study, we developed a quantitative structure-activity relationship (QSAR) model for the toxicities (half effect concentration, EC 50 ) of 45 binary and multi-component mixtures composed of two antibiotics and four pesticides. The acute toxicities of single compound and mixtures toward Aliivibrio fischeri were tested. A genetic algorithm was used to obtain the optimized model with three theoretical descriptors. Various internal and external validation techniques indicated that the coefficient of determination of 0.9366 and root mean square error of 0.1345 for the QSAR model predicted that 45 mixture toxicities presented additive, synergistic, and antagonistic effects. Compared with the traditional concentration additive and independent action models, the QSAR model exhibited an advantage in predicting mixture toxicity. Thus, the presented approach may be able to fill the gaps in predicting non-additive toxicities of binary and multi-component mixtures. Copyright © 2018 Elsevier Ltd. All rights reserved.

Flash evaporation of liquid monomer particle mixture

DOEpatents

Affinito, John D.; Darab, John G.; Gross, Mark E.

1999-01-01

The present invention is a method of making a first solid composite polymer layer. The method has the steps of (a) mixing a liquid monomer with particles substantially insoluble in the liquid monomer forming a monomer particle mixture; (b) flash evaporating the particle mixture and forming a composite vapor; and (c) continuously cryocondensing said composite vapor on a cool substrate and cross-linking the cryocondensed film thereby forming the polymer layer.

Evaluating Mixture Modeling for Clustering: Recommendations and Cautions

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2011-01-01

This article provides a large-scale investigation into several of the properties of mixture-model clustering techniques (also referred to as latent class cluster analysis, latent profile analysis, model-based clustering, probabilistic clustering, Bayesian classification, unsupervised learning, and finite mixture models; see Vermunt & Magdison,…

Development and validation of a metal mixture bioavailability model (MMBM) to predict chronic toxicity of Ni-Zn-Pb mixtures to Ceriodaphnia dubia.

PubMed

Nys, Charlotte; Janssen, Colin R; De Schamphelaere, Karel A C

2017-01-01

Recently, several bioavailability-based models have been shown to predict acute metal mixture toxicity with reasonable accuracy. However, the application of such models to chronic mixture toxicity is less well established. Therefore, we developed in the present study a chronic metal mixture bioavailability model (MMBM) by combining the existing chronic daphnid bioavailability models for Ni, Zn, and Pb with the independent action (IA) model, assuming strict non-interaction between the metals for binding at the metal-specific biotic ligand sites. To evaluate the predictive capacity of the MMBM, chronic (7d) reproductive toxicity of Ni-Zn-Pb mixtures to Ceriodaphnia dubia was investigated in four different natural waters (pH range: 7-8; Ca range: 1-2 mM; Dissolved Organic Carbon range: 5-12 mg/L). In each water, mixture toxicity was investigated at equitoxic metal concentration ratios as well as at environmental (i.e. realistic) metal concentration ratios. Statistical analysis of mixture effects revealed that observed interactive effects depended on the metal concentration ratio investigated when evaluated relative to the concentration addition (CA) model, but not when evaluated relative to the IA model. This indicates that interactive effects observed in an equitoxic experimental design cannot always be simply extrapolated to environmentally realistic exposure situations. Generally, the IA model predicted Ni-Zn-Pb mixture toxicity more accurately than the CA model. Overall, the MMBM predicted Ni-Zn-Pb mixture toxicity (expressed as % reproductive inhibition relative to a control) in 85% of the treatments with less than 20% error. Moreover, the MMBM predicted chronic toxicity of the ternary Ni-Zn-Pb mixture at least equally accurately as the toxicity of the individual metal treatments (RMSE Mix  = 16; RMSE Zn only  = 18; RMSE Ni only  = 17; RMSE Pb only  = 23). Based on the present study, we believe MMBMs can be a promising tool to account for the effects of water chemistry on metal mixture toxicity during chronic exposure and could be used in metal risk assessment frameworks. Copyright © 2016 Elsevier Ltd. All rights reserved.

Apparatus for diffusion separation

DOEpatents

Nierenberg, William A.; Pontius, Rex B.

1976-08-10

1. The method of testing the separation efficiency of porous permeable membranes which comprises causing a stream of a gaseous mixture to flow into contact with one face of a finely porous permeable membrane under such conditions that a major fraction of the mixture diffuses through the membrane, maintaining a rectangular cross section of the gaseous stream so flowing past said membrane, continuously recirculating the gas that diffuses through said membrane and continuously withdrawing the gas that does not diffuse through said membrane and maintaining the volume of said recirculating gas constant by continuously introducing into said continuously recirculating gas stream a mass of gas equivalent to that which is continuously withdrawn from said gas stream and comparing the concentrations of the light component in the entering gas, the withdrawn gas and the recirculated gas in order to determine the efficiency of said membrane.

Atomic quantum simulation of dynamical gauge fields coupled to fermionic matter: from string breaking to evolution after a quench.

PubMed

Banerjee, D; Dalmonte, M; Müller, M; Rico, E; Stebler, P; Wiese, U-J; Zoller, P

2012-10-26

Using a Fermi-Bose mixture of ultracold atoms in an optical lattice, we construct a quantum simulator for a U(1) gauge theory coupled to fermionic matter. The construction is based on quantum links which realize continuous gauge symmetry with discrete quantum variables. At low energies, quantum link models with staggered fermions emerge from a Hubbard-type model which can be quantum simulated. This allows us to investigate string breaking as well as the real-time evolution after a quench in gauge theories, which are inaccessible to classical simulation methods.

Stabilization of ammonia-rich hydrate inside icy planets.

PubMed

Naden Robinson, Victor; Wang, Yanchao; Ma, Yanming; Hermann, Andreas

2017-08-22

The interior structure of the giant ice planets Uranus and Neptune, but also of newly discovered exoplanets, is loosely constrained, because limited observational data can be satisfied with various interior models. Although it is known that their mantles comprise large amounts of water, ammonia, and methane ices, it is unclear how these organize themselves within the planets-as homogeneous mixtures, with continuous concentration gradients, or as well-separated layers of specific composition. While individual ices have been studied in great detail under pressure, the properties of their mixtures are much less explored. We show here, using first-principles calculations, that the 2:1 ammonia hydrate, (H 2 O)(NH 3 ) 2 , is stabilized at icy planet mantle conditions due to a remarkable structural evolution. Above 65 GPa, we predict it will transform from a hydrogen-bonded molecular solid into a fully ionic phase O 2- ([Formula: see text]) 2 , where all water molecules are completely deprotonated, an unexpected bonding phenomenon not seen before. Ammonia hemihydrate is stable in a sequence of ionic phases up to 500 GPa, pressures found deep within Neptune-like planets, and thus at higher pressures than any other ammonia-water mixture. This suggests it precipitates out of any ammonia-water mixture at sufficiently high pressures and thus forms an important component of icy planets.

Rasch Mixture Models for DIF Detection

PubMed Central

Strobl, Carolin; Zeileis, Achim

2014-01-01

Rasch mixture models can be a useful tool when checking the assumption of measurement invariance for a single Rasch model. They provide advantages compared to manifest differential item functioning (DIF) tests when the DIF groups are only weakly correlated with the manifest covariates available. Unlike in single Rasch models, estimation of Rasch mixture models is sensitive to the specification of the ability distribution even when the conditional maximum likelihood approach is used. It is demonstrated in a simulation study how differences in ability can influence the latent classes of a Rasch mixture model. If the aim is only DIF detection, it is not of interest to uncover such ability differences as one is only interested in a latent group structure regarding the item difficulties. To avoid any confounding effect of ability differences (or impact), a new score distribution for the Rasch mixture model is introduced here. It ensures the estimation of the Rasch mixture model to be independent of the ability distribution and thus restricts the mixture to be sensitive to latent structure in the item difficulties only. Its usefulness is demonstrated in a simulation study, and its application is illustrated in a study of verbal aggression. PMID:29795819

Investigating Stage-Sequential Growth Mixture Models with Multiphase Longitudinal Data

ERIC Educational Resources Information Center

Kim, Su-Young; Kim, Jee-Seon

2012-01-01

This article investigates three types of stage-sequential growth mixture models in the structural equation modeling framework for the analysis of multiple-phase longitudinal data. These models can be important tools for situations in which a single-phase growth mixture model produces distorted results and can allow researchers to better understand…

Mixture Modeling: Applications in Educational Psychology

ERIC Educational Resources Information Center

Harring, Jeffrey R.; Hodis, Flaviu A.

2016-01-01

Model-based clustering methods, commonly referred to as finite mixture modeling, have been applied to a wide variety of cross-sectional and longitudinal data to account for heterogeneity in population characteristics. In this article, we elucidate 2 such approaches: growth mixture modeling and latent profile analysis. Both techniques are…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alhroob, M.; Boyd, G.; Hasib, A.

Precision ultrasonic measurements in binary gas systems provide continuous real-time monitoring of mixture composition and flow. Using custom micro-controller-based electronics, we have developed an ultrasonic instrument, with numerous potential applications, capable of making continuous high-precision sound velocity measurements. The instrument measures sound transit times along two opposite directions aligned parallel to - or obliquely crossing - the gas flow. The difference between the two measured times yields the gas flow rate while their average gives the sound velocity, which can be compared with a sound velocity vs. molar composition look-up table for the binary mixture at a given temperature andmore » pressure. The look-up table may be generated from prior measurements in known mixtures of the two components, from theoretical calculations, or from a combination of the two. We describe the instrument and its performance within numerous applications in the ATLAS experiment at the CERN Large Hadron Collider (LHC). The instrument can be of interest in other areas where continuous in-situ binary gas analysis and flowmetry are required. (authors)« less

Local Solutions in the Estimation of Growth Mixture Models

ERIC Educational Resources Information Center

Hipp, John R.; Bauer, Daniel J.

2006-01-01

Finite mixture models are well known to have poorly behaved likelihood functions featuring singularities and multiple optima. Growth mixture models may suffer from fewer of these problems, potentially benefiting from the structure imposed on the estimated class means and covariances by the specified growth model. As demonstrated here, however,…

SPR imaging based electronic tongue via landscape images for complex mixture analysis.

PubMed

Genua, Maria; Garçon, Laurie-Amandine; Mounier, Violette; Wehry, Hillary; Buhot, Arnaud; Billon, Martial; Calemczuk, Roberto; Bonnaffé, David; Hou, Yanxia; Livache, Thierry

2014-12-01

Electronic noses/tongues (eN/eT) have emerged as promising alternatives for analysis of complex mixtures in the domain of food and beverage quality control. We have recently developed an electronic tongue by combining surface plasmon resonance imaging (SPRi) with an array of non-specific and cross-reactive receptors prepared by simply mixing two small molecules in varying and controlled proportions and allowing the mixtures to self-assemble on the SPRi prism surface. The obtained eT generated novel and unique 2D continuous evolution profiles (CEPs) and 3D continuous evolution landscapes (CELs) based on which the differentiation of complex mixtures such as red wine, beer and milk were successful. The preliminary experiments performed for monitoring the deterioration of UHT milk demonstrated its potential for quality control applications. Furthermore, the eT exhibited good repeatability and stability, capable of operating after a minimum storage period of 5 months. Copyright © 2014 Elsevier B.V. All rights reserved.

Damage/fault diagnosis in an operating wind turbine under uncertainty via a vibration response Gaussian mixture random coefficient model based framework

NASA Astrophysics Data System (ADS)

Avendaño-Valencia, Luis David; Fassois, Spilios D.

2017-07-01

The study focuses on vibration response based health monitoring for an operating wind turbine, which features time-dependent dynamics under environmental and operational uncertainty. A Gaussian Mixture Model Random Coefficient (GMM-RC) model based Structural Health Monitoring framework postulated in a companion paper is adopted and assessed. The assessment is based on vibration response signals obtained from a simulated offshore 5 MW wind turbine. The non-stationarity in the vibration signals originates from the continually evolving, due to blade rotation, inertial properties, as well as the wind characteristics, while uncertainty is introduced by random variations of the wind speed within the range of 10-20 m/s. Monte Carlo simulations are performed using six distinct structural states, including the healthy state and five types of damage/fault in the tower, the blades, and the transmission, with each one of them characterized by four distinct levels. Random vibration response modeling and damage diagnosis are illustrated, along with pertinent comparisons with state-of-the-art diagnosis methods. The results demonstrate consistently good performance of the GMM-RC model based framework, offering significant performance improvements over state-of-the-art methods. Most damage types and levels are shown to be properly diagnosed using a single vibration sensor.

A new insight into the dependence of relaxation time on frequency in viscoelastic surfactant solutions: From experimental to modeling study.

PubMed

García, Brayan F; Saraji, Soheil

2018-05-01

The relaxation time in viscoelastic surfactant solutions is a function of temperature, salt/surfactant concentrations, resting conditions, as well as shear frequency. The simplistic assumption of a single and constant relaxation time is not representative of all relaxation modes in these solutions especially at high frequencies. Steady-state and oscillatory measurements are carried out to study the effects of high temperature, concentration and resting condition on the rheology of surfactants/salt mixtures including a non-ionic and a zwitterionic/anionic surfactant system. Furthermore, a novel semi-empirical rheological model is deducted based on Cates theory.This model introduces, for the first time, a frequency-dependence for the continuous relaxation time spectrum. At high temperatures, the non-ionic surfactant become more viscoelastic and the zwitterionic/anionic system loses its viscoelasticity. The addition of surfactant/salt improves the viscoelasticity of both systems, and, for the zwitterionic/anionic mixture, increasing the resting temperature improves its viscoelasticity. In addition, the proposed model significantly improves predictions of traditional Maxwell model for different viscoelastic surfactant solutions (using data from this study and the literature) for a considerable range of surfactant and salt combinations at a wide range of temperature. Copyright © 2018 Elsevier Inc. All rights reserved.

Flash evaporation of liquid monomer particle mixture

DOEpatents

Affinito, J.D.; Darab, J.G.; Gross, M.E.

1999-05-11

The present invention is a method of making a first solid composite polymer layer. The method has the steps of (a) mixing a liquid monomer with particles substantially insoluble in the liquid monomer forming a monomer particle mixture; (b) flash evaporating the particle mixture and forming a composite vapor; and (c) continuously cryocondensing said composite vapor on a cool substrate and cross-linking the cryocondensed film thereby forming the polymer layer. 3 figs.

Infinite von Mises-Fisher Mixture Modeling of Whole Brain fMRI Data.

PubMed

Røge, Rasmus E; Madsen, Kristoffer H; Schmidt, Mikkel N; Mørup, Morten

2017-10-01

Cluster analysis of functional magnetic resonance imaging (fMRI) data is often performed using gaussian mixture models, but when the time series are standardized such that the data reside on a hypersphere, this modeling assumption is questionable. The consequences of ignoring the underlying spherical manifold are rarely analyzed, in part due to the computational challenges imposed by directional statistics. In this letter, we discuss a Bayesian von Mises-Fisher (vMF) mixture model for data on the unit hypersphere and present an efficient inference procedure based on collapsed Markov chain Monte Carlo sampling. Comparing the vMF and gaussian mixture models on synthetic data, we demonstrate that the vMF model has a slight advantage inferring the true underlying clustering when compared to gaussian-based models on data generated from both a mixture of vMFs and a mixture of gaussians subsequently normalized. Thus, when performing model selection, the two models are not in agreement. Analyzing multisubject whole brain resting-state fMRI data from healthy adult subjects, we find that the vMF mixture model is considerably more reliable than the gaussian mixture model when comparing solutions across models trained on different groups of subjects, and again we find that the two models disagree on the optimal number of components. The analysis indicates that the fMRI data support more than a thousand clusters, and we confirm this is not a result of overfitting by demonstrating better prediction on data from held-out subjects. Our results highlight the utility of using directional statistics to model standardized fMRI data and demonstrate that whole brain segmentation of fMRI data requires a very large number of functional units in order to adequately account for the discernible statistical patterns in the data.

SOA formation from photooxidation of naphthalene and methylnaphthalenes with m-xylene and surrogate mixtures

NASA Astrophysics Data System (ADS)

Chen, Chia-Li; Li, Lijie; Tang, Ping; Cocker, David R.

2018-05-01

SOA formation is not well predicted in current models in urban area. The interaction among multiple anthropogenic volatile organic compounds is essential for the SOA formation in the complex urban atmosphere. Secondary organic aerosol (SOA) from the photooxidation of naphthalene, 1-methylnaphthalene, and 2-methylnaphthalene as well as individual polycyclic aromatic hydrocarbons (PAHs) mixed with m-xylene or an atmospheric surrogate mixture was explored in the UCR CE-CERT environmental chamber under urban relevant low NOx and extremely low NOx (H2O2) conditions. Addition of m-xylene suppressed SOA formation from the individual PAH precursor. A similar suppression effect on SOA formation was observed during the surrogate mixture photooxidation suggesting the importance of gas-phase chemical reactivity to SOA formation. The SOA growth rate for different PAH-m-xylene mixtures was strongly correlated with initial [HO2]/[RO2] ratio but negatively correlated with initial m-xylene/NO ratio. Decreasing SOA formation was observed for increasing m-xylene/PAHs ratios and increasing initial m-xylene/NO ratio. The SOA chemical composition characteristics such as f44 versus f43, H/C ratio, O/C ratio, and the oxidation state of the carbon OSbarc were consistent with a continuously aging with the SOA exhibiting characteristics of both individual precursors. SOA formation from PAHs was also suppressed within an atmospheric surrogate mixture compared to the SOA formed from individual PAHs, indicating that atmospheric reactivity directly influences SOA formation from PAHs.

Cluster kinetics model for mixtures of glassformers

NASA Astrophysics Data System (ADS)

Brenskelle, Lisa A.; McCoy, Benjamin J.

2007-10-01

For glassformers we propose a binary mixture relation for parameters in a cluster kinetics model previously shown to represent pure compound data for viscosity and dielectric relaxation as functions of either temperature or pressure. The model parameters are based on activation energies and activation volumes for cluster association-dissociation processes. With the mixture parameters, we calculated dielectric relaxation times and compared the results to experimental values for binary mixtures. Mixtures of sorbitol and glycerol (seven compositions), sorbitol and xylitol (three compositions), and polychloroepihydrin and polyvinylmethylether (three compositions) were studied.

[Morphine-antiemetics mixtures for continuous subcutaneous infusion in terminal cancer].

PubMed

Ottesen, S; Monrad, L

1992-05-30

Simultaneous pain, nausea and vomiting are not uncommon in terminal suffering requiring treatment with various compounds of analgesics and antiemetics. At Baerum Hospital the pump reservoirs for continuous, subcutaneous drug delivery are routinely filled by the hospital pharmacist. We examined the physico-chemical stability of various concentrations of mixtures of morphine-metoclopramide and morphine-metoclopramide-haloperidol at 25 degrees C. We found good stability for at least seven days. Addition of haloperidol seems to reduce stability. Plain morphine-haloperidol solutions are unstable. Split products were not found in any of the mixtures. We also examined the osmolality of current clinical compounds, focusing on local irritant effect at the infusion site. All solutions except for one with a high concentration of haloperidol were found to be close to isoosmolarl.

Electrophoresis-mass spectrometry probe

DOEpatents

Andresen, Brian D.; Fought, Eric R.

1987-01-01

The invention involves a new technique for the separation of complex mixtures of chemicals, which utilizes a unique interface probe for conventional mass spectrometers which allows the electrophoretically separated compounds to be analyzed in real-time by a mass spectrometer. This new chemical analysis interface, which couples electrophoresis with mass spectrometry, allows complex mixtures to be analyzed very rapidly, with much greater specificity, and with greater sensitivity. The interface or probe provides a means whereby large and/or polar molecules in complex mixtures to be completely characterized. The preferred embodiment of the probe utilizes a double capillary tip which allows the probe tip to be continually wetted by the buffer, which provides for increased heat dissipation, and results in a continually operating interface which is more durable and electronically stable than the illustrated single capillary tip probe interface.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing.

PubMed

Leong, Siow Hoo; Ong, Seng Huat

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing

PubMed Central

Leong, Siow Hoo

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index. PMID:28686634

21 CFR 864.8625 - Hematology quality control mixture.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Hematology quality control mixture. 864.8625 Section 864.8625 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES HEMATOLOGY AND PATHOLOGY DEVICES Hematology Reagents § 864.8625 Hematology...

21 CFR 864.8625 - Hematology quality control mixture.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Hematology quality control mixture. 864.8625 Section 864.8625 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES HEMATOLOGY AND PATHOLOGY DEVICES Hematology Reagents § 864.8625 Hematology...

21 CFR 864.8625 - Hematology quality control mixture.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Hematology quality control mixture. 864.8625 Section 864.8625 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES HEMATOLOGY AND PATHOLOGY DEVICES Hematology Reagents § 864.8625 Hematology...

Evaluating differential effects using regression interactions and regression mixture models

PubMed Central

Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung

2015-01-01

Research increasingly emphasizes understanding differential effects. This paper focuses on understanding regression mixture models, a relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their formulation, and their assumptions are compared using Monte Carlo simulations and real data analysis. The capabilities of regression mixture models are described and specific issues to be addressed when conducting regression mixtures are proposed. The paper aims to clarify the role that regression mixtures can take in the estimation of differential effects and increase awareness of the benefits and potential pitfalls of this approach. Regression mixture models are shown to be a potentially effective exploratory method for finding differential effects when these effects can be defined by a small number of classes of respondents who share a typical relationship between a predictor and an outcome. It is also shown that the comparison between regression mixture models and interactions becomes substantially more complex as the number of classes increases. It is argued that regression interactions are well suited for direct tests of specific hypotheses about differential effects and regression mixtures provide a useful approach for exploring effect heterogeneity given adequate samples and study design. PMID:26556903

Nonlinear Structured Growth Mixture Models in M"plus" and OpenMx

ERIC Educational Resources Information Center

Grimm, Kevin J.; Ram, Nilam; Estabrook, Ryne

2010-01-01

Growth mixture models (GMMs; B. O. Muthen & Muthen, 2000; B. O. Muthen & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models…

The Potential of Growth Mixture Modelling

ERIC Educational Resources Information Center

Muthen, Bengt

2006-01-01

The authors of the paper on growth mixture modelling (GMM) give a description of GMM and related techniques as applied to antisocial behaviour. They bring up the important issue of choice of model within the general framework of mixture modelling, especially the choice between latent class growth analysis (LCGA) techniques developed by Nagin and…

Equivalence of truncated count mixture distributions and mixtures of truncated count distributions.

PubMed

Böhning, Dankmar; Kuhnert, Ronny

2006-12-01

This article is about modeling count data with zero truncation. A parametric count density family is considered. The truncated mixture of densities from this family is different from the mixture of truncated densities from the same family. Whereas the former model is more natural to formulate and to interpret, the latter model is theoretically easier to treat. It is shown that for any mixing distribution leading to a truncated mixture, a (usually different) mixing distribution can be found so that the associated mixture of truncated densities equals the truncated mixture, and vice versa. This implies that the likelihood surfaces for both situations agree, and in this sense both models are equivalent. Zero-truncated count data models are used frequently in the capture-recapture setting to estimate population size, and it can be shown that the two Horvitz-Thompson estimators, associated with the two models, agree. In particular, it is possible to achieve strong results for mixtures of truncated Poisson densities, including reliable, global construction of the unique NPMLE (nonparametric maximum likelihood estimator) of the mixing distribution, implying a unique estimator for the population size. The benefit of these results lies in the fact that it is valid to work with the mixture of truncated count densities, which is less appealing for the practitioner but theoretically easier. Mixtures of truncated count densities form a convex linear model, for which a developed theory exists, including global maximum likelihood theory as well as algorithmic approaches. Once the problem has been solved in this class, it might readily be transformed back to the original problem by means of an explicitly given mapping. Applications of these ideas are given, particularly in the case of the truncated Poisson family.

Development of PBPK Models for Gasoline in Adult and ...

EPA Pesticide Factsheets

Concern for potential developmental effects of exposure to gasoline-ethanol blends has grown along with their increased use in the US fuel supply. Physiologically-based pharmacokinetic (PBPK) models for these complex mixtures were developed to address dosimetric issues related to selection of exposure concentrations for in vivo toxicity studies. Sub-models for individual hydrocarbon (HC) constituents were first developed and calibrated with published literature or QSAR-derived data where available. Successfully calibrated sub-models for individual HCs were combined, assuming competitive metabolic inhibition in the liver, and a priori simulations of mixture interactions were performed. Blood HC concentration data were collected from exposed adult non-pregnant (NP) rats (9K ppm total HC vapor, 6h/day) to evaluate performance of the NP mixture model. This model was then converted to a pregnant (PG) rat mixture model using gestational growth equations that enabled a priori estimation of life-stage specific kinetic differences. To address the impact of changing relevant physiological parameters from NP to PG, the PG mixture model was first calibrated against the NP data. The PG mixture model was then evaluated against data from PG rats that were subsequently exposed (9K ppm/6.33h gestation days (GD) 9-20). Overall, the mixture models adequately simulated concentrations of HCs in blood from single (NP) or repeated (PG) exposures (within ~2-3 fold of measured values of

Aerobic biodegradability of methyldiethanolamine (MDEA) used in natural gas sweetening plants in batch tests and continuous flow experiments.

PubMed

Fürhacker, M; Pressl, A; Allabashi, R

2003-09-01

Mixtures of different amines including tertiary amines (methyldiethanolamine, MDEA) are commonly used for the removal of CO2 from gas mixtures or in gas sweetening processes for the extraction of CO2 and H2S. The absorber solutions used can be released into the industrial waste water due to continuous substitution of degraded MDEA, periodically cleaning processes or an accidental spill. In this study, the aerobic biodegradability of MDEA was investigated in a standardised batch test and a continuous flow experiment (40 l/d). The results of the batch test indicated that the MDEA-solution was non-biodegradable during the test period of 28 days, whereas the continuous flow experiments showed biodegradation of more than 96% based on TOC-measurements. This was probably due to the adaptation of the microorganisms to this particular waste water contamination during continuous flow experiment.

Mixture-mixture design for the fingerprint optimization of chromatographic mobile phases and extraction solutions for Camellia sinensis.

PubMed

Borges, Cleber N; Bruns, Roy E; Almeida, Aline A; Scarminio, Ieda S

2007-07-09

A composite simplex centroid-simplex centroid mixture design is proposed for simultaneously optimizing two mixture systems. The complementary model is formed by multiplying special cubic models for the two systems. The design was applied to the simultaneous optimization of both mobile phase chromatographic mixtures and extraction mixtures for the Camellia sinensis Chinese tea plant. The extraction mixtures investigated contained varying proportions of ethyl acetate, ethanol and dichloromethane while the mobile phase was made up of varying proportions of methanol, acetonitrile and a methanol-acetonitrile-water (MAW) 15%:15%:70% mixture. The experiments were block randomized corresponding to a split-plot error structure to minimize laboratory work and reduce environmental impact. Coefficients of an initial saturated model were obtained using Scheffe-type equations. A cumulative probability graph was used to determine an approximate reduced model. The split-plot error structure was then introduced into the reduced model by applying generalized least square equations with variance components calculated using the restricted maximum likelihood approach. A model was developed to calculate the number of peaks observed with the chromatographic detector at 210 nm. A 20-term model contained essentially all the statistical information of the initial model and had a root mean square calibration error of 1.38. The model was used to predict the number of peaks eluted in chromatograms obtained from extraction solutions that correspond to axial points of the simplex centroid design. The significant model coefficients are interpreted in terms of interacting linear, quadratic and cubic effects of the mobile phase and extraction solution components.

Reduced detonation kinetics and detonation structure in one- and multi-fuel gaseous mixtures

NASA Astrophysics Data System (ADS)

Fomin, P. A.; Trotsyuk, A. V.; Vasil'ev, A. A.

2017-10-01

Two-step approximate models of chemical kinetics of detonation combustion of (i) one-fuel (CH4/air) and (ii) multi-fuel gaseous mixtures (CH4/H2/air and CH4/CO/air) are developed for the first time. The models for multi-fuel mixtures are proposed for the first time. Owing to the simplicity and high accuracy, the models can be used in multi-dimensional numerical calculations of detonation waves in corresponding gaseous mixtures. The models are in consistent with the second law of thermodynamics and Le Chatelier’s principle. Constants of the models have a clear physical meaning. Advantages of the kinetic model for detonation combustion of methane has been demonstrated via numerical calculations of a two-dimensional structure of the detonation wave in a stoichiometric and fuel-rich methane-air mixtures and stoichiometric methane-oxygen mixture. The dominant size of the detonation cell, determines in calculations, is in good agreement with all known experimental data.

Fitting a Mixture Item Response Theory Model to Personality Questionnaire Data: Characterizing Latent Classes and Investigating Possibilities for Improving Prediction

ERIC Educational Resources Information Center

Maij-de Meij, Annette M.; Kelderman, Henk; van der Flier, Henk

2008-01-01

Mixture item response theory (IRT) models aid the interpretation of response behavior on personality tests and may provide possibilities for improving prediction. Heterogeneity in the population is modeled by identifying homogeneous subgroups that conform to different measurement models. In this study, mixture IRT models were applied to the…

Observation of twinning in diamond CVD films

NASA Astrophysics Data System (ADS)

Marciniak, W.; Fabisiak, K.; Orzeszko, S.; Rozploch, F.

1992-10-01

Diamond particles prepared by dc-glow-discharge enhanced HF-CVD hybrid method, from a mixture of acetone vapor and hydrogen gas have been examined by TEM, RHEED and dark field method of observation. Results suggest the presence of twinned diamond particles, which can be reconstructed by a sequence of twinning operations. Contrary to the 'stick model' of the lattice, very common five-fold symmetry of diamond microcrystals may be obtained by applying a number of edge dislocations rather than the continuous deformation of many tetrahedral C-C bonds.

Continuation of superpave projects monitoring.

DOT National Transportation Integrated Search

2011-07-01

This study involved the continuous monitoring of material properties and field performance of : twelve Superpave project sections in Florida for the establishment of reasonable and effective mixture : design guidelines and criteria, the identificatio...

Leads Detection Using Mixture Statistical Distribution Based CRF Algorithm from Sentinel-1 Dual Polarization SAR Imagery

NASA Astrophysics Data System (ADS)

Zhang, Yu; Li, Fei; Zhang, Shengkai; Zhu, Tingting

2017-04-01

Synthetic Aperture Radar (SAR) is significantly important for polar remote sensing since it can provide continuous observations in all days and all weather. SAR can be used for extracting the surface roughness information characterized by the variance of dielectric properties and different polarization channels, which make it possible to observe different ice types and surface structure for deformation analysis. In November, 2016, Chinese National Antarctic Research Expedition (CHINARE) 33rd cruise has set sails in sea ice zone in Antarctic. Accurate leads spatial distribution in sea ice zone for routine planning of ship navigation is essential. In this study, the semantic relationship between leads and sea ice categories has been described by the Conditional Random Fields (CRF) model, and leads characteristics have been modeled by statistical distributions in SAR imagery. In the proposed algorithm, a mixture statistical distribution based CRF is developed by considering the contexture information and the statistical characteristics of sea ice for improving leads detection in Sentinel-1A dual polarization SAR imagery. The unary potential and pairwise potential in CRF model is constructed by integrating the posteriori probability estimated from statistical distributions. For mixture statistical distribution parameter estimation, Method of Logarithmic Cumulants (MoLC) is exploited for single statistical distribution parameters estimation. The iteration based Expectation Maximal (EM) algorithm is investigated to calculate the parameters in mixture statistical distribution based CRF model. In the posteriori probability inference, graph-cut energy minimization method is adopted in the initial leads detection. The post-processing procedures including aspect ratio constrain and spatial smoothing approaches are utilized to improve the visual result. The proposed method is validated on Sentinel-1A SAR C-band Extra Wide Swath (EW) Ground Range Detected (GRD) imagery with a pixel spacing of 40 meters near Prydz Bay area, East Antarctica. Main work is listed as follows: 1) A mixture statistical distribution based CRF algorithm has been developed for leads detection from Sentinel-1A dual polarization images. 2) The assessment of the proposed mixture statistical distribution based CRF method and single distribution based CRF algorithm has been presented. 3) The preferable parameters sets including statistical distributions, the aspect ratio threshold and spatial smoothing window size have been provided. In the future, the proposed algorithm will be developed for the operational Sentinel series data sets processing due to its less time consuming cost and high accuracy in leads detection.

3-D Numerical Simulation for Gas-Liquid Two-Phase Flow in Aeration Tank

NASA Astrophysics Data System (ADS)

Xue, R.; Tian, R.; Yan, S. Y.; Li, S.

In the crafts of activated sludge treatment, oxygen supply and the suspending state of activated sludge are primary factors to keep biochemistry process carrying on normally. However, they are all controlled by aeration. So aeration is crucial. The paper focus on aeration, use CFD software to simulate the field of aeration tank which is designed by sludge load method. The main designed size of aeration tank is: total volume: 20 000 m3; corridor width: 8m; total length of corridors: 139m; number of corridors: 3; length of one single corridor: 48m; effective depth: 4.5m; additional depth: 0.5m. According to the similarity theory, a geometrical model is set up in proportion of 10:1. The way of liquid flow is submerge to avoid liquid flow out directly. The grid is plotted by dividing the whole computational area into two parts. The bottom part which contains gas pipe and gas exit hole and the above part which is the main area are plotted by tetrahedron and hexahedron respectively. In boundary conditions, gas is defined as the primary-phase, and liquid is defined as the secondary-phase. Choosing mixture model, two-phase flow field of aeration tank is simulated by solved the Continuity equation for the mixture, Momentum equation for the mixture, Volume fraction equation for the secondary phases and Relative velocity formula when gas velocity is 10m/s, 20m/s, 30m/s. what figure shows is the contour of velocity magnitude for the mixture phase when gas velocity is 20m/s. Through analysis, the simulation tendency is agreed with actual running of aeration tank. It is feasible to use mixture model to simulate flow field of aeration tank by fluent software. According to the simulation result, the better velocity of liquid or gas (the quantity of inlet air) can be chosen by lower cost, and also the performance of aeration tank can be forecast. It will be helpful for designing and operation.

Coal-water mixture fuel burner

DOEpatents

Brown, T.D.; Reehl, D.P.; Walbert, G.F.

1985-04-29

The present invention represents an improvement over the prior art by providing a rotating cup burner arrangement for use with a coal-water mixture fuel which applies a thin, uniform sheet of fuel onto the inner surface of the rotating cup, inhibits the collection of unburned fuel on the inner surface of the cup, reduces the slurry to a collection of fine particles upon discharge from the rotating cup, and further atomizes the fuel as it enters the combustion chamber by subjecting it to the high shear force of a high velocity air flow. Accordingly, it is an object of the present invention to provide for improved combustion of a coal-water mixture fuel. It is another object of the present invention to provide an arrangement for introducing a coal-water mixture fuel into a combustion chamber in a manner which provides improved flame control and stability, more efficient combustion of the hydrocarbon fuel, and continuous, reliable burner operation. Yet another object of the present invention is to provide for the continuous, sustained combustion of a coal-water mixture fuel without the need for a secondary combustion source such as natural gas or a liquid hydrocarbon fuel. Still another object of the present invention is to provide a burner arrangement capable of accommodating a coal-water mixture fuel having a wide range of rheological and combustion characteristics in providing for its efficient combustion. 7 figs.

Investigation on Constrained Matrix Factorization for Hyperspectral Image Analysis

DTIC Science & Technology

2005-07-25

analysis. Keywords: matrix factorization; nonnegative matrix factorization; linear mixture model ; unsupervised linear unmixing; hyperspectral imagery...spatial resolution permits different materials present in the area covered by a single pixel. The linear mixture model says that a pixel reflectance in...in r. In the linear mixture model , r is considered as the linear mixture of m1, m2, …, mP as nMαr += (1) where n is included to account for

Mixed Convective Condensation in Enclosures with Noncondensable Gases

NASA Astrophysics Data System (ADS)

Fox, Richard John

1994-01-01

A transient, two-dimensional, numerical model was developed in order to study the laminar flow, heat, and mass transfer in a vertical reflux condenser loaded with vapor and noncondensable gas. The simplified model treats the two-component (gas/vapor), two-phase (vapor/liquid) mixture as a continuum by making use of conservation equations for mass continuity, momentum, species, and energy. The liquid mist phase is formed in such a way as to obey one of three conditions: thermodynamic equilibrium, complete nonequilibrium (no mist formation), or partial equilibrium (partial supersaturation). In developing the model, special attention was paid to the formulation of the boundary conditions, global continuity, and numerical efficiency. Two different mixture combinations were used in order to create stable and unstable systems. Steam-helium mixtures (Mv, = 18, Mg = 4) were found to exhibit stable flows with the lighter helium trapped in the upper portion of the condenser, shutting off condensation in that region. Steam-air mixtures (M_ {v}, = 18, Mg = 28) were found to exhibit varying degrees of instability, depending on the noncondensable gas and heat load, owing to the accumulation of the heavy gas near the condensing surface. Under low gas loading cases (Pg = 0.031 kg/m^3) the natural convective fluctuations were found to be weak and the flow was more easily dominated by the forced convective inlet flow and wall suction. At such low gas loadings, stable, asymmetric flow patterns persisted up to high powers. Large gas loadings (Pg = 0.196 kg/m^3) showed much stronger natural convective effects. Regions of counterflowing vapor and gas were found to promote stronger mixing as the power was increased. Regions of noncondensing gas were found to blanket the condenser walls as the suction velocity increased, resulting in a strong resistance to heat and mass transfer and consequent increase in system pressure. Moderate gas loadings (Pg = 0.065 kg/m ^3) were found to exhibit intermediate behavior between the low and high gas loading cases. For the moderate gas loading cases, a bifurcation was found to occur when Re was increased beyond a critical value, forcing the system into one of two stable, distinct flow patterns. Each branch of the bifurcation was found to correspond to the flows that occur in either the low or high gas loading cases, and radically different heat transfer performance was encountered for the same system parameters. The model was also used to simulate experiments conducted in a vertical reflux thermosyphon using steam -air mixtures. The qualitative aspects of the flow were in reasonable agreement between the model and experiment and trends in the local heat transfer were similar. By converting latent heat energy into sensible heat energy, mist formation was found to increase the system temperature and, as a consequence, the overall heat transfer coefficient was lowered. However, the total heat transfer rate was not sensitive to mist formation since the reduction in the latent heat transfer was accompanied by a corresponding increase in the sensible heat transfer, altering the mode but not the magnitude of the total heat transfer.

40 CFR 716.105 - Additions of substances and mixtures to which this subpart applies.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 31 2014-07-01 2014-07-01 false Additions of substances and mixtures to which this subpart applies. 716.105 Section 716.105 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT HEALTH AND SAFETY DATA REPORTING Specific Chemical...

40 CFR 716.105 - Additions of substances and mixtures to which this subpart applies.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Additions of substances and mixtures to which this subpart applies. 716.105 Section 716.105 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT HEALTH AND SAFETY DATA REPORTING Specific Chemical...

40 CFR 716.105 - Additions of substances and mixtures to which this subpart applies.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 31 2011-07-01 2011-07-01 false Additions of substances and mixtures to which this subpart applies. 716.105 Section 716.105 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT HEALTH AND SAFETY DATA REPORTING Specific Chemical...

40 CFR 716.105 - Additions of substances and mixtures to which this subpart applies.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 32 2012-07-01 2012-07-01 false Additions of substances and mixtures to which this subpart applies. 716.105 Section 716.105 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT HEALTH AND SAFETY DATA REPORTING Specific Chemical...

40 CFR 716.105 - Additions of substances and mixtures to which this subpart applies.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 32 2013-07-01 2013-07-01 false Additions of substances and mixtures to which this subpart applies. 716.105 Section 716.105 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT HEALTH AND SAFETY DATA REPORTING Specific Chemical...

Gene Expression Responses in Male Fathead Minnows Exposed to Binary Mixtures of an Estrogen and Antiestrogen

EPA Science Inventory

Aquatic organisms are continuously exposed to complex mixtures of chemicals, many of which can interfere with their endocrine system, resulting in impaired reproduction, development or survival, among others. In order to analyze the effects and mechanisms of action of estrogen...

Microstructure and hydrogen bonding in water-acetonitrile mixtures.

PubMed

Mountain, Raymond D

2010-12-16

The connection of hydrogen bonding between water and acetonitrile in determining the microheterogeneity of the liquid mixture is examined using NPT molecular dynamics simulations. Mixtures for six, rigid, three-site models for acetonitrile and one water model (SPC/E) were simulated to determine the amount of water-acetonitrile hydrogen bonding. Only one of the six acetonitrile models (TraPPE-UA) was able to reproduce both the liquid density and the experimental estimates of hydrogen bonding derived from Raman scattering of the CN stretch band or from NMR quadrupole relaxation measurements. A simple modification of the acetonitrile model parameters for the models that provided poor estimates produced hydrogen-bonding results consistent with experiments for two of the models. Of these, only one of the modified models also accurately determined the density of the mixtures. The self-diffusion coefficient of liquid acetonitrile provided a final winnowing of the modified model and the successful, unmodified model. The unmodified model is provisionally recommended for simulations of water-acetonitrile mixtures.

General mixture item response models with different item response structures: Exposition with an application to Likert scales.

PubMed

Tijmstra, Jesper; Bolsinova, Maria; Jeon, Minjeong

2018-01-10

This article proposes a general mixture item response theory (IRT) framework that allows for classes of persons to differ with respect to the type of processes underlying the item responses. Through the use of mixture models, nonnested IRT models with different structures can be estimated for different classes, and class membership can be estimated for each person in the sample. If researchers are able to provide competing measurement models, this mixture IRT framework may help them deal with some violations of measurement invariance. To illustrate this approach, we consider a two-class mixture model, where a person's responses to Likert-scale items containing a neutral middle category are either modeled using a generalized partial credit model, or through an IRTree model. In the first model, the middle category ("neither agree nor disagree") is taken to be qualitatively similar to the other categories, and is taken to provide information about the person's endorsement. In the second model, the middle category is taken to be qualitatively different and to reflect a nonresponse choice, which is modeled using an additional latent variable that captures a person's willingness to respond. The mixture model is studied using simulation studies and is applied to an empirical example.

Analysis of Two-Phase Flow in Damper Seals for Cryogenic Turbopumps

NASA Technical Reports Server (NTRS)

Arauz, Grigory L.; SanAndres, Luis

1996-01-01

Cryogenic damper seals operating close to the liquid-vapor region (near the critical point or slightly su-cooled) are likely to present two-phase flow conditions. Under single phase flow conditions the mechanical energy conveyed to the fluid increases its temperature and causes a phase change when the fluid temperature reaches the saturation value. A bulk-flow analysis for the prediction of the dynamic force response of damper seals operating under two-phase conditions is presented as: all-liquid, liquid-vapor, and all-vapor, i.e. a 'continuous vaporization' model. The two phase region is considered as a homogeneous saturated mixture in thermodynamic equilibrium. Th flow in each region is described by continuity, momentum and energy transport equations. The interdependency of fluid temperatures and pressure in the two-phase region (saturated mixture) does not allow the use of an energy equation in terms of fluid temperature. Instead, the energy transport is expressed in terms of fluid enthalpy. Temperature in the single phase regions, or mixture composition in the two phase region are determined based on the fluid enthalpy. The flow is also regarded as adiabatic since the large axial velocities typical of the seal application determine small levels of heat conduction to the walls as compared to the heat carried by fluid advection. Static and dynamic force characteristics for the seal are obtained from a perturbation analysis of the governing equations. The solution expressed in terms of zeroth and first order fields provide the static (leakage, torque, velocity, pressure, temperature, and mixture composition fields) and dynamic (rotordynamic force coefficients) seal parameters. Theoretical predictions show good agreement with experimental leakage pressure profiles, available from a Nitrogen at cryogenic temperatures. Force coefficient predictions for two phase flow conditions show significant fluid compressibility effects, particularly for mixtures with low mass content of vapor. Under these conditions, an increase on direct stiffness and reduction of whirl frequency ratio are shown to occur. Prediction of such important effects will motivate experimental studies as well as a more judicious selection of the operating conditions for seals used in cryogenic turbomachinery.

Using low-field NMR to infer the physical properties of glassy oligosaccharide/water mixtures.

PubMed

Aeberhardt, Kasia; Bui, Quang D; Normand, Valéry

2007-03-01

Low-field NMR (LF-NMR) is usually used as an analytical technique, for instance, to determine water and oil contents. For this application, no attempt is made to understand the physical origin of the data. Here we build a physical model to explain the five fit parameters of the conventional free induction decay (FID) for glassy oligosaccharide/water mixtures. The amplitudes of the signals from low-mobility and high-mobility protons correspond to the density of oligosaccharide protons and water protons, respectively. The relaxation time of the high-mobility protons is described using a statistical model for the probability that oligosaccharide hydroxyl groups form multiple hydrogen bonds. The variation of energy of the hydrogen bond is calculated from the average bond distance and the average angle contribution. Applying the model to experimental data shows that hydrogen atoms screen the water oxygen atoms when two water molecules solvate a single hydroxyl group. Furthermore, the relaxation time of the oligosaccharide protons is independent of its molecular weight and the water content. Finally, inversion of the FID using the inverse Laplace transform gives the continuous spectrum of relaxation times, which is a fingerprint of the oligosaccharide.

Low Mach number fluctuating hydrodynamics for electrolytes

NASA Astrophysics Data System (ADS)

Péraud, Jean-Philippe; Nonaka, Andy; Chaudhri, Anuj; Bell, John B.; Donev, Aleksandar; Garcia, Alejandro L.

2016-11-01

We formulate and study computationally the low Mach number fluctuating hydrodynamic equations for electrolyte solutions. We are interested in studying transport in mixtures of charged species at the mesoscale, down to scales below the Debye length, where thermal fluctuations have a significant impact on the dynamics. Continuing our previous work on fluctuating hydrodynamics of multicomponent mixtures of incompressible isothermal miscible liquids [A. Donev et al., Phys. Fluids 27, 037103 (2015), 10.1063/1.4913571], we now include the effect of charged species using a quasielectrostatic approximation. Localized charges create an electric field, which in turn provides additional forcing in the mass and momentum equations. Our low Mach number formulation eliminates sound waves from the fully compressible formulation and leads to a more computationally efficient quasi-incompressible formulation. We demonstrate our ability to model saltwater (NaCl) solutions in both equilibrium and nonequilibrium settings. We show that our algorithm is second order in the deterministic setting and for length scales much greater than the Debye length gives results consistent with an electroneutral approximation. In the stochastic setting, our model captures the predicted dynamics of equilibrium and nonequilibrium fluctuations. We also identify and model an instability that appears when diffusive mixing occurs in the presence of an applied electric field.

Applications of the Simple Multi-Fluid Model to Correlations of the Vapor-Liquid Equilibrium of Refrigerant Mixtures Containing Carbon Dioxide

NASA Astrophysics Data System (ADS)

Akasaka, Ryo

This study presents a simple multi-fluid model for Helmholtz energy equations of state. The model contains only three parameters, whereas rigorous multi-fluid models developed for several industrially important mixtures usually have more than 10 parameters and coefficients. Therefore, the model can be applied to mixtures where experimental data is limited. Vapor-liquid equilibrium (VLE) of the following seven mixtures have been successfully correlated with the model: CO2 + difluoromethane (R-32), CO2 + trifluoromethane (R-23), CO2 + fluoromethane (R-41), CO2 + 1,1,1,2- tetrafluoroethane (R-134a), CO2 + pentafluoroethane (R-125), CO2 + 1,1-difluoroethane (R-152a), and CO2 + dimethyl ether (DME). The best currently available equations of state for the pure refrigerants were used for the correlations. For all mixtures, average deviations in calculated bubble-point pressures from experimental values are within 2%. The simple multi-fluid model will be helpful for design and simulations of heat pumps and refrigeration systems using the mixtures as working fluid.

Continuation of superpave projects monitoring.

DOT National Transportation Integrated Search

2011-07-01

This study involved the continuous monitoring of material properties and field performance of twelve Superpave project sections in Florida for the establishment of reasonable and effective mixture design guidelines and criteria, the identification an...

Different Approaches to Covariate Inclusion in the Mixture Rasch Model

ERIC Educational Resources Information Center

Li, Tongyun; Jiao, Hong; Macready, George B.

2016-01-01

The present study investigates different approaches to adding covariates and the impact in fitting mixture item response theory models. Mixture item response theory models serve as an important methodology for tackling several psychometric issues in test development, including the detection of latent differential item functioning. A Monte Carlo…

A compressibility based model for predicting the tensile strength of directly compressed pharmaceutical powder mixtures.

PubMed

Reynolds, Gavin K; Campbell, Jacqueline I; Roberts, Ron J

2017-10-05

A new model to predict the compressibility and compactability of mixtures of pharmaceutical powders has been developed. The key aspect of the model is consideration of the volumetric occupancy of each powder under an applied compaction pressure and the respective contribution it then makes to the mixture properties. The compressibility and compactability of three pharmaceutical powders: microcrystalline cellulose, mannitol and anhydrous dicalcium phosphate have been characterised. Binary and ternary mixtures of these excipients have been tested and used to demonstrate the predictive capability of the model. Furthermore, the model is shown to be uniquely able to capture a broad range of mixture behaviours, including neutral, negative and positive deviations, illustrating its utility for formulation design. Copyright © 2017 Elsevier B.V. All rights reserved.

Dissipation-Induced Anomalous Multicritical Phenomena

NASA Astrophysics Data System (ADS)

Soriente, M.; Donner, T.; Chitra, R.; Zilberberg, O.

2018-05-01

We explore the influence of dissipation on a paradigmatic driven-dissipative model where a collection of two level atoms interact with both quadratures of a quantum cavity mode. The closed system exhibits multiple phase transitions involving discrete and continuous symmetries breaking and all phases culminate in a multicritical point. In the open system, we show that infinitesimal dissipation erases the phase with broken continuous symmetry and radically alters the model's phase diagram. The multicritical point now becomes brittle and splits into two tricritical points where first- and second-order symmetry-breaking transitions meet. A quantum fluctuations analysis shows that, surprisingly, the tricritical points exhibit anomalous finite fluctuations, as opposed to standard tricritical points arising in He 3 -He 4 mixtures. Our work has direct implications for a variety of fields, including cold atoms and ions in optical cavities, circuit-quantum electrodynamics as well as optomechanical systems.

Extracting Spurious Latent Classes in Growth Mixture Modeling with Nonnormal Errors

ERIC Educational Resources Information Center

Guerra-Peña, Kiero; Steinley, Douglas

2016-01-01

Growth mixture modeling is generally used for two purposes: (1) to identify mixtures of normal subgroups and (2) to approximate oddly shaped distributions by a mixture of normal components. Often in applied research this methodology is applied to both of these situations indistinctly: using the same fit statistics and likelihood ratio tests. This…

Electrophoresis-mass spectrometry probe

DOEpatents

Andresen, B.D.; Fought, E.R.

1987-11-10

The invention involves a new technique for the separation of complex mixtures of chemicals, which utilizes a unique interface probe for conventional mass spectrometers which allows the electrophoretically separated compounds to be analyzed in real-time by a mass spectrometer. This new chemical analysis interface, which couples electrophoresis with mass spectrometry, allows complex mixtures to be analyzed very rapidly, with much greater specificity, and with greater sensitivity. The interface or probe provides a means whereby large and/or polar molecules in complex mixtures to be completely characterized. The preferred embodiment of the probe utilizes a double capillary tip which allows the probe tip to be continually wetted by the buffer, which provides for increased heat dissipation, and results in a continually operating interface which is more durable and electronically stable than the illustrated single capillary tip probe interface. 8 figs.

Investigating the Impact of Item Parameter Drift for Item Response Theory Models with Mixture Distributions.

PubMed

Park, Yoon Soo; Lee, Young-Sun; Xing, Kuan

2016-01-01

This study investigates the impact of item parameter drift (IPD) on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT) models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS) were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results also showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effects on item parameters and examinee ability.

Investigating the Impact of Item Parameter Drift for Item Response Theory Models with Mixture Distributions

PubMed Central

Park, Yoon Soo; Lee, Young-Sun; Xing, Kuan

2016-01-01

This study investigates the impact of item parameter drift (IPD) on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT) models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS) were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results also showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effects on item parameters and examinee ability. PMID:26941699

Solubility modeling of refrigerant/lubricant mixtures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Michels, H.H.; Sienel, T.H.

1996-12-31

A general model for predicting the solubility properties of refrigerant/lubricant mixtures has been developed based on applicable theory for the excess Gibbs energy of non-ideal solutions. In our approach, flexible thermodynamic forms are chosen to describe the properties of both the gas and liquid phases of refrigerant/lubricant mixtures. After an extensive study of models for describing non-ideal liquid effects, the Wohl-suffix equations, which have been extensively utilized in the analysis of hydrocarbon mixtures, have been developed into a general form applicable to mixtures where one component is a POE lubricant. In the present study we have analyzed several POEs wheremore » structural and thermophysical property data were available. Data were also collected from several sources on the solubility of refrigerant/lubricant binary pairs. We have developed a computer code (NISC), based on the Wohl model, that predicts dew point or bubble point conditions over a wide range of composition and temperature. Our present analysis covers mixtures containing up to three refrigerant molecules and one lubricant. The present code can be used to analyze the properties of R-410a and R-407c in mixtures with a POE lubricant. Comparisons with other models, such as the Wilson or modified Wilson equations, indicate that the Wohl-suffix equations yield more reliable predictions for HFC/POE mixtures.« less

Auditory steady state responses and cochlear implants: Modeling the artifact-response mixture in the perspective of denoising

PubMed Central

Mina, Faten; Attina, Virginie; Duroc, Yvan; Veuillet, Evelyne; Truy, Eric; Thai-Van, Hung

2017-01-01

Auditory steady state responses (ASSRs) in cochlear implant (CI) patients are contaminated by the spread of a continuous CI electrical stimulation artifact. The aim of this work was to model the electrophysiological mixture of the CI artifact and the corresponding evoked potentials on scalp electrodes in order to evaluate the performance of denoising algorithms in eliminating the CI artifact in a controlled environment. The basis of the proposed computational framework is a neural mass model representing the nodes of the auditory pathways. Six main contributors to auditory evoked potentials from the cochlear level and up to the auditory cortex were taken into consideration. The simulated dynamics were then projected into a 3-layer realistic head model. 32-channel scalp recordings of the CI artifact-response were then generated by solving the electromagnetic forward problem. As an application, the framework’s simulated 32-channel datasets were used to compare the performance of 4 commonly used Independent Component Analysis (ICA) algorithms: infomax, extended infomax, jade and fastICA in eliminating the CI artifact. As expected, two major components were detectable in the simulated datasets, a low frequency component at the modulation frequency and a pulsatile high frequency component related to the stimulation frequency. The first can be attributed to the phase-locked ASSR and the second to the stimulation artifact. Among the ICA algorithms tested, simulations showed that infomax was the most efficient and reliable in denoising the CI artifact-response mixture. Denoising algorithms can induce undesirable deformation of the signal of interest in real CI patient recordings. The proposed framework is a valuable tool for evaluating these algorithms in a controllable environment ahead of experimental or clinical applications. PMID:28350887

Auditory steady state responses and cochlear implants: Modeling the artifact-response mixture in the perspective of denoising.

PubMed

Mina, Faten; Attina, Virginie; Duroc, Yvan; Veuillet, Evelyne; Truy, Eric; Thai-Van, Hung

2017-01-01

Auditory steady state responses (ASSRs) in cochlear implant (CI) patients are contaminated by the spread of a continuous CI electrical stimulation artifact. The aim of this work was to model the electrophysiological mixture of the CI artifact and the corresponding evoked potentials on scalp electrodes in order to evaluate the performance of denoising algorithms in eliminating the CI artifact in a controlled environment. The basis of the proposed computational framework is a neural mass model representing the nodes of the auditory pathways. Six main contributors to auditory evoked potentials from the cochlear level and up to the auditory cortex were taken into consideration. The simulated dynamics were then projected into a 3-layer realistic head model. 32-channel scalp recordings of the CI artifact-response were then generated by solving the electromagnetic forward problem. As an application, the framework's simulated 32-channel datasets were used to compare the performance of 4 commonly used Independent Component Analysis (ICA) algorithms: infomax, extended infomax, jade and fastICA in eliminating the CI artifact. As expected, two major components were detectable in the simulated datasets, a low frequency component at the modulation frequency and a pulsatile high frequency component related to the stimulation frequency. The first can be attributed to the phase-locked ASSR and the second to the stimulation artifact. Among the ICA algorithms tested, simulations showed that infomax was the most efficient and reliable in denoising the CI artifact-response mixture. Denoising algorithms can induce undesirable deformation of the signal of interest in real CI patient recordings. The proposed framework is a valuable tool for evaluating these algorithms in a controllable environment ahead of experimental or clinical applications.

Post-flight Analysis of the Argon Filled Ion Chamber

NASA Technical Reports Server (NTRS)

Tai, H.; Goldhagen, P.; Jones, I. W.; Wilson, J. W.; Maiden, D. L.; Shinn, J. L.

2003-01-01

Atmospheric ionizing radiation is a complex mixture of primary galactic and solar cosmic rays and a multitude of secondary particles produced in collision with air nuclei. The first series of Atmospheric Ionizing Radiation (AIR) measurement flights on the NASA research aircraft ER-2 took place in June 1997. The ER-2 flight package consisted of fifteen instruments from six countries and were chosen to provide varying sensitivity to specific components. These AIR ER-2 flight measurements are to characterize the AIR environment during solar minimum to allow the continued development of environmental models of this complex mixture of ionizing radiation. This will enable scientists to study the ionizing radiation health hazard associated with the high-altitude operation of a commercial supersonic transport and to allow estimates of single event upsets for advanced avionics systems design. The argon filled ion chamber representing about 40 percent of the contributions to radiation risks are analyzed herein and model discrepancies for solar minimum environment are on the order of 5 percent and less. Other biologically significant components remain to be analyzed.

Lead Time Demand Modeling in Continuous Review Supply Chain Models

DTIC Science & Technology

2013-04-01

International Journal of Production Economics , 101, 89–98. Lin, Y. (2008). Minimax distribution free procedure with backorder price discount. International ...stochastic setting. International Journal of Production Economics , 115, 248–259. ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ã= dê~Çì~íÉ=pÅÜççä=çÑ=_ìëáåÉëë=C=mìÄäáÅ... Journal of Production Economics , 111, 118–128. Moral, S., Rumí, R., & Salmerón, A. (2001). Mixtures

Response of selected plant and insect species to simulated solid rocket exhaust mixtures and to exhaust components from solid rocket fuels

NASA Technical Reports Server (NTRS)

Heck, W. W.; Knott, W. M.; Stahel, E. P.; Ambrose, J. T.; Mccrimmon, J. N.; Engle, M.; Romanow, L. A.; Sawyer, A. G.; Tyson, J. D.

1980-01-01

The effects of solid rocket fuel (SRF) exhaust on selected plant and and insect species in the Merritt Island, Florida area was investigated in order to determine if the exhaust clouds generated by shuttle launches would adversely affect the native, plants of the Merritt Island Wildlife Refuge, the citrus production, or the beekeeping industry of the island. Conditions were simulated in greenhouse exposure chambers and field chambers constructed to model the ideal continuous stirred tank reactor. A plant exposure system was developed for dispensing and monitoring the two major chemicals in SRF exhaust, HCl and Al203, and for dispensing and monitoring SRF exhaust (controlled fuel burns). Plants native to Merritt Island, Florida were grown and used as test species. Dose-response relationships were determined for short term exposure of selected plant species to HCl, Al203, and mixtures of the two to SRF exhaust.

Turbulence hierarchy in a random fibre laser

PubMed Central

González, Iván R. Roa; Lima, Bismarck C.; Pincheira, Pablo I. R.; Brum, Arthur A.; Macêdo, Antônio M. S.; Vasconcelos, Giovani L.; de S. Menezes, Leonardo; Raposo, Ernesto P.; Gomes, Anderson S. L.; Kashyap, Raman

2017-01-01

Turbulence is a challenging feature common to a wide range of complex phenomena. Random fibre lasers are a special class of lasers in which the feedback arises from multiple scattering in a one-dimensional disordered cavity-less medium. Here we report on statistical signatures of turbulence in the distribution of intensity fluctuations in a continuous-wave-pumped erbium-based random fibre laser, with random Bragg grating scatterers. The distribution of intensity fluctuations in an extensive data set exhibits three qualitatively distinct behaviours: a Gaussian regime below threshold, a mixture of two distributions with exponentially decaying tails near the threshold and a mixture of distributions with stretched-exponential tails above threshold. All distributions are well described by a hierarchical stochastic model that incorporates Kolmogorov’s theory of turbulence, which includes energy cascade and the intermittence phenomenon. Our findings have implications for explaining the remarkably challenging turbulent behaviour in photonics, using a random fibre laser as the experimental platform. PMID:28561064

An evaluation of the Bayesian approach to fitting the N-mixture model for use with pseudo-replicated count data

USGS Publications Warehouse

Toribo, S.G.; Gray, B.R.; Liang, S.

2011-01-01

The N-mixture model proposed by Royle in 2004 may be used to approximate the abundance and detection probability of animal species in a given region. In 2006, Royle and Dorazio discussed the advantages of using a Bayesian approach in modelling animal abundance and occurrence using a hierarchical N-mixture model. N-mixture models assume replication on sampling sites, an assumption that may be violated when the site is not closed to changes in abundance during the survey period or when nominal replicates are defined spatially. In this paper, we studied the robustness of a Bayesian approach to fitting the N-mixture model for pseudo-replicated count data. Our simulation results showed that the Bayesian estimates for abundance and detection probability are slightly biased when the actual detection probability is small and are sensitive to the presence of extra variability within local sites.

Process Dissociation and Mixture Signal Detection Theory

ERIC Educational Resources Information Center

DeCarlo, Lawrence T.

2008-01-01

The process dissociation procedure was developed in an attempt to separate different processes involved in memory tasks. The procedure naturally lends itself to a formulation within a class of mixture signal detection models. The dual process model is shown to be a special case. The mixture signal detection model is applied to data from a widely…

Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research

ERIC Educational Resources Information Center

de Jong, Martijn G.; Steenkamp, Jan-Benedict E. M.

2010-01-01

We present a class of finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research. Our model is proposed for confirmatory research settings. Our prior for item parameters is a mixture distribution to accommodate situations where different groups of countries have different measurement operations, while…

Identifying common donors in DNA mixtures, with applications to database searches.

PubMed

Slooten, K

2017-01-01

Several methods exist to compute the likelihood ratio LR(M, g) evaluating the possible contribution of a person of interest with genotype g to a mixed trace M. In this paper we generalize this LR to a likelihood ratio LR(M 1 , M 2 ) involving two possibly mixed traces M 1 and M 2 , where the question is whether there is a donor in common to both traces. In case one of the traces is in fact a single genotype, then this likelihood ratio reduces to the usual LR(M, g). We explain how our method conceptually is a logical consequence of the fact that LR calculations of the form LR(M, g) can be equivalently regarded as a probabilistic deconvolution of the mixture. Based on simulated data, and using a semi-continuous mixture evaluation model, we derive ROC curves of our method applied to various types of mixtures. From these data we conclude that searches for a common donor are often feasible in the sense that a very small false positive rate can be combined with a high probability to detect a common donor if there is one. We also show how database searches comparing all traces to each other can be carried out efficiently, as illustrated by the application of the method to the mixed traces in the Dutch DNA database. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

40 CFR 716.45 - How to report on substances and mixtures.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 31 2011-07-01 2011-07-01 false How to report on substances and mixtures. 716.45 Section 716.45 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT HEALTH AND SAFETY DATA REPORTING General Provisions § 716.45 How to report on...

40 CFR 716.45 - How to report on substances and mixtures.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 31 2014-07-01 2014-07-01 false How to report on substances and mixtures. 716.45 Section 716.45 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT HEALTH AND SAFETY DATA REPORTING General Provisions § 716.45 How to report on...

40 CFR 716.45 - How to report on substances and mixtures.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 32 2012-07-01 2012-07-01 false How to report on substances and mixtures. 716.45 Section 716.45 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT HEALTH AND SAFETY DATA REPORTING General Provisions § 716.45 How to report on...

40 CFR 716.45 - How to report on substances and mixtures.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false How to report on substances and mixtures. 716.45 Section 716.45 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT HEALTH AND SAFETY DATA REPORTING General Provisions § 716.45 How to report on...

40 CFR 716.45 - How to report on substances and mixtures.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 32 2013-07-01 2013-07-01 false How to report on substances and mixtures. 716.45 Section 716.45 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT HEALTH AND SAFETY DATA REPORTING General Provisions § 716.45 How to report on...

Inhalation Toxicology. X., Times to incapacitation for rats exposed continuously to carbon monoxide, acrolein, and to carbon monoxide-acrolein mixtures.

DOT National Transportation Integrated Search

1990-12-01

Laboratory rats were exposed to experimental atmospheres of (a) carbon monoxide (CO) in air, (b) acrolein in air, and (c) to mixtures of CO and acrolein in air. The toxic potency of each of the three types of environments was evaluated toxicokinetica...

30 CFR 75.334 - Worked-out areas and areas where pillars are being recovered.

Code of Federal Regulations, 2011 CFR

2011-07-01

... be used to control spontaneous combustion, accumulations of methane-air mixtures, and other gases... pillars have been recovered shall be— (1) Ventilated so that methane-air mixtures and other gases, dusts... be used to control the air passing through the area and to continuously dilute and move methane-air...

30 CFR 75.334 - Worked-out areas and areas where pillars are being recovered.

Code of Federal Regulations, 2010 CFR

2010-07-01

... be used to control spontaneous combustion, accumulations of methane-air mixtures, and other gases... pillars have been recovered shall be— (1) Ventilated so that methane-air mixtures and other gases, dusts... be used to control the air passing through the area and to continuously dilute and move methane-air...

30 CFR 75.334 - Worked-out areas and areas where pillars are being recovered.

Code of Federal Regulations, 2013 CFR

2013-07-01

... be used to control spontaneous combustion, accumulations of methane-air mixtures, and other gases... pillars have been recovered shall be— (1) Ventilated so that methane-air mixtures and other gases, dusts... be used to control the air passing through the area and to continuously dilute and move methane-air...

30 CFR 75.334 - Worked-out areas and areas where pillars are being recovered.

Code of Federal Regulations, 2014 CFR

2014-07-01

... be used to control spontaneous combustion, accumulations of methane-air mixtures, and other gases... pillars have been recovered shall be— (1) Ventilated so that methane-air mixtures and other gases, dusts... be used to control the air passing through the area and to continuously dilute and move methane-air...

30 CFR 75.334 - Worked-out areas and areas where pillars are being recovered.

Code of Federal Regulations, 2012 CFR

2012-07-01

... be used to control spontaneous combustion, accumulations of methane-air mixtures, and other gases... pillars have been recovered shall be— (1) Ventilated so that methane-air mixtures and other gases, dusts... be used to control the air passing through the area and to continuously dilute and move methane-air...

33 CFR 155.360 - Oily mixture (bilge slops) discharges on oceangoing ships of 400 gross tons and above but less...

Code of Federal Regulations, 2010 CFR

2010-07-01

... Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) POLLUTION OIL OR HAZARDOUS MATERIAL POLLUTION PREVENTION REGULATIONS FOR VESSELS Vessel Equipment § 155.360 Oily mixture (bilge slops... the date of its initial survey prior to receiving its International Oil Pollution Prevention (IOPP...

ENVIRONMENTAL ASSESSMENT OF A FIRETUBE BOILER FIRING COAL/OIL/WATER MIXTURES. VOLUME 1. TECHNICAL RESULTS

EPA Science Inventory

This volume describes emission results from sampling of flue gas from a firetube boiler burning a coal/oil/water (COW) mixture and COW with soda ash added (COW+SA) to control SO2 emissions. Measurements included: continuous monitoring of flue gas emissions; source assessment samp...

Approximation of the breast height diameter distribution of two-cohort stands by mixture models I Parameter estimation

Treesearch

Rafal Podlaski; Francis A. Roesch

2013-01-01

Study assessed the usefulness of various methods for choosing the initial values for the numerical procedures for estimating the parameters of mixture distributions and analysed variety of mixture models to approximate empirical diameter at breast height (dbh) distributions. Two-component mixtures of either the Weibull distribution or the gamma distribution were...

Detection of mastitis in dairy cattle by use of mixture models for repeated somatic cell scores: a Bayesian approach via Gibbs sampling.

PubMed

Odegård, J; Jensen, J; Madsen, P; Gianola, D; Klemetsdal, G; Heringstad, B

2003-11-01

The distribution of somatic cell scores could be regarded as a mixture of at least two components depending on a cow's udder health status. A heteroscedastic two-component Bayesian normal mixture model with random effects was developed and implemented via Gibbs sampling. The model was evaluated using datasets consisting of simulated somatic cell score records. Somatic cell score was simulated as a mixture representing two alternative udder health statuses ("healthy" or "diseased"). Animals were assigned randomly to the two components according to the probability of group membership (Pm). Random effects (additive genetic and permanent environment), when included, had identical distributions across mixture components. Posterior probabilities of putative mastitis were estimated for all observations, and model adequacy was evaluated using measures of sensitivity, specificity, and posterior probability of misclassification. Fitting different residual variances in the two mixture components caused some bias in estimation of parameters. When the components were difficult to disentangle, so were their residual variances, causing bias in estimation of Pm and of location parameters of the two underlying distributions. When all variance components were identical across mixture components, the mixture model analyses returned parameter estimates essentially without bias and with a high degree of precision. Including random effects in the model increased the probability of correct classification substantially. No sizable differences in probability of correct classification were found between models in which a single cow effect (ignoring relationships) was fitted and models where this effect was split into genetic and permanent environmental components, utilizing relationship information. When genetic and permanent environmental effects were fitted, the between-replicate variance of estimates of posterior means was smaller because the model accounted for random genetic drift.

Assessing variation in life-history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists.

PubMed

Hamel, Sandra; Yoccoz, Nigel G; Gaillard, Jean-Michel

2017-05-01

Mixed models are now well-established methods in ecology and evolution because they allow accounting for and quantifying within- and between-individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi-modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life-history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life-history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long-term studies of large mammals to illustrate the potential of using mixture models for assessing within-population variation in life-history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life-history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users. © 2016 Cambridge Philosophical Society.

Oxidative particle mixtures for groundwater treatment

DOEpatents

Siegrist, Robert L.; Murdoch, Lawrence C.

2000-01-01

The invention is a method and a composition of a mixture for degradation and immobilization of contaminants in soil and groundwater. The oxidative particle mixture and method includes providing a material having a minimal volume of free water, mixing at least one inorganic oxidative chemical in a granular form with a carrier fluid containing a fine grained inorganic hydrophilic compound and injecting the resulting mixture into the subsurface. The granular form of the inorganic oxidative chemical dissolves within the areas of injection, and the oxidative ions move by diffusion and/or advection, therefore extending the treatment zone over a wider area than the injection area. The organic contaminants in the soil and groundwater are degraded by the oxidative ions, which form solid byproducts that can sorb significant amounts of inorganic contaminants, metals, and radionuclides for in situ treatment and immobilization of contaminants. The method and composition of the oxidative particle mixture for long-term treatment and immobilization of contaminants in soil and groundwater provides for a reduction in toxicity of contaminants in a subsurface area of contamination without the need for continued injection of treatment material, or for movement of the contaminants, or without the need for continuous pumping of groundwater through the treatment zone, or removal of groundwater from the subsurface area of contamination.

SI-traceable and dynamic reference gas mixtures for water vapour at polar and high troposphere atmospheric levels

NASA Astrophysics Data System (ADS)

Guillevic, Myriam; Pascale, Céline; Mutter, Daniel; Wettstein, Sascha; Niederhauser, Bernhard

2017-04-01

In the framework of METAS' AtmoChem-ECV project, new facilities are currently being developed to generate reference gas mixtures for water vapour at concentrations measured in the high troposphere and polar regions, in the range 1-20 µmol/mol (ppm). The generation method is dynamic (the mixture is produced continuously over time) and SI-traceable (i.e. the amount of substance fraction in mole per mole is traceable to the definition of SI-units). The generation process is composed of three successive steps. The first step is to purify the matrix gas, nitrogen or synthetic air. Second, this matrix gas is spiked with the pure substance using a permeation technique: a permeation device contains a few grams of pure water in liquid form and loses it linearly over time by permeation through a membrane. In a third step, to reach the desired concentration, the first, high concentration mixture exiting the permeation chamber is then diluted with a chosen flow of matrix gas with one or two subsequent dilution steps. All flows are piloted by mass flow controllers. All parts in contact with the gas mixture are passivated using coated surfaces, to reduce adsorption/desorption processes as much as possible. The mixture can eventually be directly used to calibrate an analyser. The standard mixture produced by METAS' dynamic setup was injected into a chilled mirror from MBW Calibration AG, the designated institute for absolute humidity calibration in Switzerland. The used chilled mirror, model 373LX, is able to measure frost point and sample pressure and therefore calculate the water vapour concentration. This intercomparison of the two systems was performed in the range 4-18 ppm water vapour in synthetic air, at two different pressure levels, 1013.25 hPa and 2000 hPa. We present here METAS' dynamic setup, its uncertainty budget and the first results of the intercomparison with MBW's chilled mirror.

Modelling diameter distributions of two-cohort forest stands with various proportions of dominant species: a two-component mixture model approach.

Treesearch

Rafal Podlaski; Francis Roesch

2014-01-01

In recent years finite-mixture models have been employed to approximate and model empirical diameter at breast height (DBH) distributions. We used two-component mixtures of either the Weibull distribution or the gamma distribution for describing the DBH distributions of mixed-species, two-cohort forest stands, to analyse the relationships between the DBH components,...

Modeling mixtures of thyroid gland function disruptors in a vertebrate alternative model, the zebrafish eleutheroembryo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thienpont, Benedicte; Barata, Carlos; Raldúa, Demetrio, E-mail: drpqam@cid.csic.es

2013-06-01

Maternal thyroxine (T4) plays an essential role in fetal brain development, and even mild and transitory deficits in free-T4 in pregnant women can produce irreversible neurological effects in their offspring. Women of childbearing age are daily exposed to mixtures of chemicals disrupting the thyroid gland function (TGFDs) through the diet, drinking water, air and pharmaceuticals, which has raised the highest concern for the potential additive or synergic effects on the development of mild hypothyroxinemia during early pregnancy. Recently we demonstrated that zebrafish eleutheroembryos provide a suitable alternative model for screening chemicals impairing the thyroid hormone synthesis. The present study usedmore » the intrafollicular T4-content (IT4C) of zebrafish eleutheroembryos as integrative endpoint for testing the hypotheses that the effect of mixtures of TGFDs with a similar mode of action [inhibition of thyroid peroxidase (TPO)] was well predicted by a concentration addition concept (CA) model, whereas the response addition concept (RA) model predicted better the effect of dissimilarly acting binary mixtures of TGFDs [TPO-inhibitors and sodium-iodide symporter (NIS)-inhibitors]. However, CA model provided better prediction of joint effects than RA in five out of the six tested mixtures. The exception being the mixture MMI (TPO-inhibitor)-KClO{sub 4} (NIS-inhibitor) dosed at a fixed ratio of EC{sub 10} that provided similar CA and RA predictions and hence it was difficult to get any conclusive result. There results support the phenomenological similarity criterion stating that the concept of concentration addition could be extended to mixture constituents having common apical endpoints or common adverse outcomes. - Highlights: • Potential synergic or additive effect of mixtures of chemicals on thyroid function. • Zebrafish as alternative model for testing the effect of mixtures of goitrogens. • Concentration addition seems to predict better the effect of mixtures of goitrogens.« less

Removal of NO in NO/N2, NO/N2/O2, NO/CH4/N2, and NO/CH4/O2/N2 systems by flowing microwave discharges.

PubMed

Hueso, José L; Gonzalez-Elipe, Agustín R; Cotrino, José; Caballero, Alfonso

2007-02-15

In this paper, continuing previous work, we report on experiments carried out to investigate the removal of NO from simulated flue gas in nonthermal plasmas. The plasma-induced decomposition of small concentrations of NO in N2 used as the carrier gas and O2 and CH4 as minority components has been studied in a surface wave discharge induced with a surfatron launcher. The reaction products and efficiency have been monitored by mass spectrometry as a function of the composition of the mixture. NO is effectively decomposed into N2 and O2 even in the presence of O2, provided always that enough CH4 is also present in the mixture. Other majority products of the plasma reactions under these conditions are NH3, CO, and H2. In the absence of O2, decomposition of NO also occurs, although in that case HCN accompanies the other reaction products as a majority component. The plasma for the different reaction mixtures has been characterized by optical emission spectroscopy. Intermediate excited species of NO*, C*, CN*, NH*, and CH* have been monitored depending on the gas mixture. The type of species detected and their evolution with the gas composition are in agreement with the reaction products detected in each case. The observations by mass spectrometry and optical emission spectroscopy are in agreement with the kinetic reaction models available in literature for simple plasma reactions in simple reaction mixtures.

Integration of chemical and toxicological tools to assess the bioavailability of copper derived from different copper-based fungicides in soil.

PubMed

Wang, Quan-Ying; Sun, Jing-Yue; Xu, Xing-Jian; Yu, Hong-Wen

2018-06-20

Because the extensive use of Cu-based fungicides, the accumulation of Cu in agricultural soil has been widely reported. However, little information is known about the bioavailability of Cu deriving from different fungicides in soil. This paper investigated both the distribution behaviors of Cu from two commonly used fungicides (Bordeaux mixture and copper oxychloride) during the aging process and the toxicological effects of Cu on earthworms. Copper nitrate was selected as a comparison during the aging process. The distribution process of exogenous Cu into different soil fractions involved an initial rapid retention (the first 8 weeks) and a following slow continuous retention. Moreover, Cu mainly moved from exchangeable and carbonate fractions to Fe-Mn oxides-combined fraction during the aging process. The Elovich model fit well with the available Cu aging process, and the transformation rate was in the order of Cu(NO 3 ) 2 > Bordeaux mixture > copper oxychloride. On the other hand, the biological responses of earthworms showed that catalase activities and malondialdehyde contents of the copper oxychloride treated earthworms were significantly higher than those of Bordeaux mixture treated earthworms. Also, body Cu loads of earthworms from different Cu compounds spiked soils were in the following order: copper oxychloride > Bordeaux mixture. Thus, the bioavailability of Cu from copper oxychloride in soil was significantly higher than that of Bordeaux mixture, and different Cu compounds should be taken into consideration when studying the bioavailability of Cu-based fungicides in the soil. Copyright © 2018 Elsevier Inc. All rights reserved.

Bayesian spatiotemporal crash frequency models with mixture components for space-time interactions.

PubMed

Cheng, Wen; Gill, Gurdiljot Singh; Zhang, Yongping; Cao, Zhong

2018-03-01

The traffic safety research has developed spatiotemporal models to explore the variations in the spatial pattern of crash risk over time. Many studies observed notable benefits associated with the inclusion of spatial and temporal correlation and their interactions. However, the safety literature lacks sufficient research for the comparison of different temporal treatments and their interaction with spatial component. This study developed four spatiotemporal models with varying complexity due to the different temporal treatments such as (I) linear time trend; (II) quadratic time trend; (III) Autoregressive-1 (AR-1); and (IV) time adjacency. Moreover, the study introduced a flexible two-component mixture for the space-time interaction which allows greater flexibility compared to the traditional linear space-time interaction. The mixture component allows the accommodation of global space-time interaction as well as the departures from the overall spatial and temporal risk patterns. This study performed a comprehensive assessment of mixture models based on the diverse criteria pertaining to goodness-of-fit, cross-validation and evaluation based on in-sample data for predictive accuracy of crash estimates. The assessment of model performance in terms of goodness-of-fit clearly established the superiority of the time-adjacency specification which was evidently more complex due to the addition of information borrowed from neighboring years, but this addition of parameters allowed significant advantage at posterior deviance which subsequently benefited overall fit to crash data. The Base models were also developed to study the comparison between the proposed mixture and traditional space-time components for each temporal model. The mixture models consistently outperformed the corresponding Base models due to the advantages of much lower deviance. For cross-validation comparison of predictive accuracy, linear time trend model was adjudged the best as it recorded the highest value of log pseudo marginal likelihood (LPML). Four other evaluation criteria were considered for typical validation using the same data for model development. Under each criterion, observed crash counts were compared with three types of data containing Bayesian estimated, normal predicted, and model replicated ones. The linear model again performed the best in most scenarios except one case of using model replicated data and two cases involving prediction without including random effects. These phenomena indicated the mediocre performance of linear trend when random effects were excluded for evaluation. This might be due to the flexible mixture space-time interaction which can efficiently absorb the residual variability escaping from the predictable part of the model. The comparison of Base and mixture models in terms of prediction accuracy further bolstered the superiority of the mixture models as the mixture ones generated more precise estimated crash counts across all four models, suggesting that the advantages associated with mixture component at model fit were transferable to prediction accuracy. Finally, the residual analysis demonstrated the consistently superior performance of random effect models which validates the importance of incorporating the correlation structures to account for unobserved heterogeneity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Response Mixture Modeling: Accounting for Heterogeneity in Item Characteristics across Response Times.

PubMed

Molenaar, Dylan; de Boeck, Paul

2018-06-01

In item response theory modeling of responses and response times, it is commonly assumed that the item responses have the same characteristics across the response times. However, heterogeneity might arise in the data if subjects resort to different response processes when solving the test items. These differences may be within-subject effects, that is, a subject might use a certain process on some of the items and a different process with different item characteristics on the other items. If the probability of using one process over the other process depends on the subject's response time, within-subject heterogeneity of the item characteristics across the response times arises. In this paper, the method of response mixture modeling is presented to account for such heterogeneity. Contrary to traditional mixture modeling where the full response vectors are classified, response mixture modeling involves classification of the individual elements in the response vector. In a simulation study, the response mixture model is shown to be viable in terms of parameter recovery. In addition, the response mixture model is applied to a real dataset to illustrate its use in investigating within-subject heterogeneity in the item characteristics across response times.

Zero-gravity growth of a sodium chloride-lithium fluoride eutectic mixture

NASA Technical Reports Server (NTRS)

Yue, A. S.; Yeh, C. W.; Yue, B. K.

1982-01-01

Continuous and discontinuous lithium fluoride fibers embedded in a sodium chloride matrix were produced in space and on Earth, respectively. The production of continuous fibers in a eutectic mixture was attributed to the absence of convective current in the liquid during solidification in space. Image transmission and optical transmittance measurements of transverse sections of the space-grown and Earth-grown ingots were made with a light microscope and a spectrometer. It was found that better optical properties were obtained from samples grown in space. This was attributed to a better alignment of lithium fluoride fibers along the growth direction.

A stochastic evolutionary model generating a mixture of exponential distributions

NASA Astrophysics Data System (ADS)

Fenner, Trevor; Levene, Mark; Loizou, George

2016-02-01

Recent interest in human dynamics has stimulated the investigation of the stochastic processes that explain human behaviour in various contexts, such as mobile phone networks and social media. In this paper, we extend the stochastic urn-based model proposed in [T. Fenner, M. Levene, G. Loizou, J. Stat. Mech. 2015, P08015 (2015)] so that it can generate mixture models, in particular, a mixture of exponential distributions. The model is designed to capture the dynamics of survival analysis, traditionally employed in clinical trials, reliability analysis in engineering, and more recently in the analysis of large data sets recording human dynamics. The mixture modelling approach, which is relatively simple and well understood, is very effective in capturing heterogeneity in data. We provide empirical evidence for the validity of the model, using a data set of popular search engine queries collected over a period of 114 months. We show that the survival function of these queries is closely matched by the exponential mixture solution for our model.

Structure-reactivity modeling using mixture-based representation of chemical reactions.

PubMed

Polishchuk, Pavel; Madzhidov, Timur; Gimadiev, Timur; Bodrov, Andrey; Nugmanov, Ramil; Varnek, Alexandre

2017-09-01

We describe a novel approach of reaction representation as a combination of two mixtures: a mixture of reactants and a mixture of products. In turn, each mixture can be encoded using an earlier reported approach involving simplex descriptors (SiRMS). The feature vector representing these two mixtures results from either concatenated product and reactant descriptors or the difference between descriptors of products and reactants. This reaction representation doesn't need an explicit labeling of a reaction center. The rigorous "product-out" cross-validation (CV) strategy has been suggested. Unlike the naïve "reaction-out" CV approach based on a random selection of items, the proposed one provides with more realistic estimation of prediction accuracy for reactions resulting in novel products. The new methodology has been applied to model rate constants of E2 reactions. It has been demonstrated that the use of the fragment control domain applicability approach significantly increases prediction accuracy of the models. The models obtained with new "mixture" approach performed better than those required either explicit (Condensed Graph of Reaction) or implicit (reaction fingerprints) reaction center labeling.

Numerical study of He/CF{sub 3}I pulsed discharge used to produce iodine atom in chemical oxygen-iodine laser

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang Jiao; Wang Yanhui; Wang Dezhen

2013-04-15

The pulsed discharge for producing iodine atoms from the alkyl and perfluoroalky iodides (CH{sub 3}I, CF{sub 3}I, etc.) is the most efficient method for achieving the pulse operating mode of a chemical oxygen-iodine laser. In this paper, a one-dimensional fluid model is developed to study the characteristics of pulsed discharge in CF{sub 3}I-He mixture. By solving continuity equation, momentum equation, Poisson equation, Boltzmann equation, and an electric circuit equation, the temporal evolution of discharge current density and various discharge products, especially the atomic iodine, are investigated. The dependence of iodine atom density on discharge parameters is also studied. The resultsmore » show that iodine atom density increases with the pulsed width and pulsed voltage amplitude. The mixture ratio of CF{sub 3}I and helium plays a more significant role in iodine atom production. For a constant voltage amplitude, there exists an optimal mixture ratio under which the maximum iodine atom concentration is achieved. The bigger the applied voltage amplitude is, the higher partial pressure of CF{sub 3}I is needed to obtain the maximum iodine atom concentration.« less

An NCME Instructional Module on Latent DIF Analysis Using Mixture Item Response Models

ERIC Educational Resources Information Center

Cho, Sun-Joo; Suh, Youngsuk; Lee, Woo-yeol

2016-01-01

The purpose of this ITEMS module is to provide an introduction to differential item functioning (DIF) analysis using mixture item response models. The mixture item response models for DIF analysis involve comparing item profiles across latent groups, instead of manifest groups. First, an overview of DIF analysis based on latent groups, called…

A Systematic Investigation of Within-Subject and Between-Subject Covariance Structures in Growth Mixture Models

ERIC Educational Resources Information Center

Liu, Junhui

2012-01-01

The current study investigated how between-subject and within-subject variance-covariance structures affected the detection of a finite mixture of unobserved subpopulations and parameter recovery of growth mixture models in the context of linear mixed-effects models. A simulation study was conducted to evaluate the impact of variance-covariance…

Effects of three veterinary antibiotics and their binary mixtures on two green alga species.

PubMed

Carusso, S; Juárez, A B; Moretton, J; Magdaleno, A

2018-03-01

The individual and combined toxicities of chlortetracycline (CTC), oxytetracycline (OTC) and enrofloxacin (ENF) have been examined in two green algae representative of the freshwater environment, the international standard strain Pseudokichneriella subcapitata and the native strain Ankistrodesmus fusiformis. The toxicities of the three antibiotics and their mixtures were similar in both strains, although low concentrations of ENF and CTC + ENF were more toxic in A. fusiformis than in the standard strain. The toxicological interactions of binary mixtures were predicted using the two classical models of additivity: Concentration Addition (CA) and Independent Action (IA), and compared to the experimentally determined toxicities over a range of concentrations between 0.1 and 10 mg L -1 . The CA model predicted the inhibition of algal growth in the three mixtures in P. subcapitata, and in the CTC + OTC and CTC + ENF mixtures in A. fusiformis. However, this model underestimated the experimental results obtained in the OTC + ENF mixture in A. fusiformis. The IA model did not predict the experimental toxicological effects of the three mixtures in either strain. The sum of the toxic units (TU) for the mixtures was calculated. According to these values, the binary mixtures CTC + ENF and OTC + ENF showed an additive effect, and the CTC + OTC mixture showed antagonism in P. subcapitata, whereas the three mixtures showed synergistic effects in A. fusiformis. Although A. fusiformis was isolated from a polluted river, it showed a similar sensitivity with respect to P. subcapitata when it was exposed to binary mixtures of antibiotics. Copyright © 2017 Elsevier Ltd. All rights reserved.

Polynomial mixture method of solving ordinary differential equations

NASA Astrophysics Data System (ADS)

Shahrir, Mohammad Shazri; Nallasamy, Kumaresan; Ratnavelu, Kuru; Kamali, M. Z. M.

2017-11-01

In this paper, a numerical solution of fuzzy quadratic Riccati differential equation is estimated using a proposed new approach that provides mixture of polynomials where iteratively the right mixture will be generated. This mixture provide a generalized formalism of traditional Neural Networks (NN). Previous works have shown reliable results using Runge-Kutta 4th order (RK4). This can be achieved by solving the 1st Order Non-linear Differential Equation (ODE) that is found commonly in Riccati differential equation. Research has shown improved results relatively to the RK4 method. It can be said that Polynomial Mixture Method (PMM) shows promising results with the advantage of continuous estimation and improved accuracy that can be produced over Mabood et al, RK-4, Multi-Agent NN and Neuro Method (NM).

The relationship between multilevel models and non-parametric multilevel mixture models: Discrete approximation of intraclass correlation, random coefficient distributions, and residual heteroscedasticity.

PubMed

Rights, Jason D; Sterba, Sonya K

2016-11-01

Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.

Method and apparatus for continuous annular electrochromatography

DOEpatents

Scott, Charles D.

1987-01-01

Separation of complex mixtures and solutions can be carried out using a method and apparatus for continuous annular electrochromatography. Solutes are diverted radially by an imposed electrical field as they move downward in a rotating chromatographic column.

Inferring network structure in non-normal and mixed discrete-continuous genomic data.

PubMed

Bhadra, Anindya; Rao, Arvind; Baladandayuthapani, Veerabhadran

2018-03-01

Inferring dependence structure through undirected graphs is crucial for uncovering the major modes of multivariate interaction among high-dimensional genomic markers that are potentially associated with cancer. Traditionally, conditional independence has been studied using sparse Gaussian graphical models for continuous data and sparse Ising models for discrete data. However, there are two clear situations when these approaches are inadequate. The first occurs when the data are continuous but display non-normal marginal behavior such as heavy tails or skewness, rendering an assumption of normality inappropriate. The second occurs when a part of the data is ordinal or discrete (e.g., presence or absence of a mutation) and the other part is continuous (e.g., expression levels of genes or proteins). In this case, the existing Bayesian approaches typically employ a latent variable framework for the discrete part that precludes inferring conditional independence among the data that are actually observed. The current article overcomes these two challenges in a unified framework using Gaussian scale mixtures. Our framework is able to handle continuous data that are not normal and data that are of mixed continuous and discrete nature, while still being able to infer a sparse conditional sign independence structure among the observed data. Extensive performance comparison in simulations with alternative techniques and an analysis of a real cancer genomics data set demonstrate the effectiveness of the proposed approach. © 2017, The International Biometric Society.

Inferring network structure in non-normal and mixed discrete-continuous genomic data

PubMed Central

Bhadra, Anindya; Rao, Arvind; Baladandayuthapani, Veerabhadran

2017-01-01

Inferring dependence structure through undirected graphs is crucial for uncovering the major modes of multivariate interaction among high-dimensional genomic markers that are potentially associated with cancer. Traditionally, conditional independence has been studied using sparse Gaussian graphical models for continuous data and sparse Ising models for discrete data. However, there are two clear situations when these approaches are inadequate. The first occurs when the data are continuous but display non-normal marginal behavior such as heavy tails or skewness, rendering an assumption of normality inappropriate. The second occurs when a part of the data is ordinal or discrete (e.g., presence or absence of a mutation) and the other part is continuous (e.g., expression levels of genes or proteins). In this case, the existing Bayesian approaches typically employ a latent variable framework for the discrete part that precludes inferring conditional independence among the data that are actually observed. The current article overcomes these two challenges in a unified framework using Gaussian scale mixtures. Our framework is able to handle continuous data that are not normal and data that are of mixed continuous and discrete nature, while still being able to infer a sparse conditional sign independence structure among the observed data. Extensive performance comparison in simulations with alternative techniques and an analysis of a real cancer genomics data set demonstrate the effectiveness of the proposed approach. PMID:28437848

Continuous electrophoretic purification of individual analytes from multicomponent mixtures.

PubMed

McLaren, David G; Chen, David D Y

2004-04-15

Individual analytes can be isolated from multicomponent mixtures and collected in the outlet vial by carrying out electrophoretic purification through a capillary column. Desired analytes are allowed to migrate continuously through the column under the electric field while undesired analytes are confined to the inlet vial by application of a hydrodynamic counter pressure. Using pressure ramping and buffer replenishment techniques, 18% of the total amount present in a bulk sample can be purified when the resolution to the adjacent peak is approximately 3. With a higher resolution, the yield could be further improved. Additionally, by periodically introducing fresh buffer into the sample, changes in pH and conductivity can be mediated, allowing higher purity (>or=99.5%) to be preserved in the collected fractions. With an additional reversed cycle of flow counterbalanced capillary electrophoresis, any individual component in a sample mixture can be purified providing it can be separated in an electrophoresis system.

General Blending Models for Data From Mixture Experiments

PubMed Central

Brown, L.; Donev, A. N.; Bissett, A. C.

2015-01-01

We propose a new class of models providing a powerful unification and extension of existing statistical methodology for analysis of data obtained in mixture experiments. These models, which integrate models proposed by Scheffé and Becker, extend considerably the range of mixture component effects that may be described. They become complex when the studied phenomenon requires it, but remain simple whenever possible. This article has supplementary material online. PMID:26681812

Application of physicochemical properties and process parameters in the development of a neural network model for prediction of tablet characteristics.

PubMed

Sovány, Tamás; Papós, Kitti; Kása, Péter; Ilič, Ilija; Srčič, Stane; Pintye-Hódi, Klára

2013-06-01

The importance of in silico modeling in the pharmaceutical industry is continuously increasing. The aim of the present study was the development of a neural network model for prediction of the postcompressional properties of scored tablets based on the application of existing data sets from our previous studies. Some important process parameters and physicochemical characteristics of the powder mixtures were used as training factors to achieve the best applicability in a wide range of possible compositions. The results demonstrated that, after some pre-processing of the factors, an appropriate prediction performance could be achieved. However, because of the poor extrapolation capacity, broadening of the training data range appears necessary.

Flexible mixture modeling via the multivariate t distribution with the Box-Cox transformation: an alternative to the skew-t distribution

PubMed Central

Lo, Kenneth

2011-01-01

Cluster analysis is the automated search for groups of homogeneous observations in a data set. A popular modeling approach for clustering is based on finite normal mixture models, which assume that each cluster is modeled as a multivariate normal distribution. However, the normality assumption that each component is symmetric is often unrealistic. Furthermore, normal mixture models are not robust against outliers; they often require extra components for modeling outliers and/or give a poor representation of the data. To address these issues, we propose a new class of distributions, multivariate t distributions with the Box-Cox transformation, for mixture modeling. This class of distributions generalizes the normal distribution with the more heavy-tailed t distribution, and introduces skewness via the Box-Cox transformation. As a result, this provides a unified framework to simultaneously handle outlier identification and data transformation, two interrelated issues. We describe an Expectation-Maximization algorithm for parameter estimation along with transformation selection. We demonstrate the proposed methodology with three real data sets and simulation studies. Compared with a wealth of approaches including the skew-t mixture model, the proposed t mixture model with the Box-Cox transformation performs favorably in terms of accuracy in the assignment of observations, robustness against model misspecification, and selection of the number of components. PMID:22125375

Flexible mixture modeling via the multivariate t distribution with the Box-Cox transformation: an alternative to the skew-t distribution.

PubMed

Lo, Kenneth; Gottardo, Raphael

2012-01-01

Cluster analysis is the automated search for groups of homogeneous observations in a data set. A popular modeling approach for clustering is based on finite normal mixture models, which assume that each cluster is modeled as a multivariate normal distribution. However, the normality assumption that each component is symmetric is often unrealistic. Furthermore, normal mixture models are not robust against outliers; they often require extra components for modeling outliers and/or give a poor representation of the data. To address these issues, we propose a new class of distributions, multivariate t distributions with the Box-Cox transformation, for mixture modeling. This class of distributions generalizes the normal distribution with the more heavy-tailed t distribution, and introduces skewness via the Box-Cox transformation. As a result, this provides a unified framework to simultaneously handle outlier identification and data transformation, two interrelated issues. We describe an Expectation-Maximization algorithm for parameter estimation along with transformation selection. We demonstrate the proposed methodology with three real data sets and simulation studies. Compared with a wealth of approaches including the skew-t mixture model, the proposed t mixture model with the Box-Cox transformation performs favorably in terms of accuracy in the assignment of observations, robustness against model misspecification, and selection of the number of components.

Mixed-up trees: the structure of phylogenetic mixtures.

PubMed

Matsen, Frederick A; Mossel, Elchanan; Steel, Mike

2008-05-01

In this paper, we apply new geometric and combinatorial methods to the study of phylogenetic mixtures. The focus of the geometric approach is to describe the geometry of phylogenetic mixture distributions for the two state random cluster model, which is a generalization of the two state symmetric (CFN) model. In particular, we show that the set of mixture distributions forms a convex polytope and we calculate its dimension; corollaries include a simple criterion for when a mixture of branch lengths on the star tree can mimic the site pattern frequency vector of a resolved quartet tree. Furthermore, by computing volumes of polytopes we can clarify how "common" non-identifiable mixtures are under the CFN model. We also present a new combinatorial result which extends any identifiability result for a specific pair of trees of size six to arbitrary pairs of trees. Next we present a positive result showing identifiability of rates-across-sites models. Finally, we answer a question raised in a previous paper concerning "mixed branch repulsion" on trees larger than quartet trees under the CFN model.

Extensions of D-optimal Minimal Designs for Symmetric Mixture Models

PubMed Central

Raghavarao, Damaraju; Chervoneva, Inna

2017-01-01

The purpose of mixture experiments is to explore the optimum blends of mixture components, which will provide desirable response characteristics in finished products. D-optimal minimal designs have been considered for a variety of mixture models, including Scheffé's linear, quadratic, and cubic models. Usually, these D-optimal designs are minimally supported since they have just as many design points as the number of parameters. Thus, they lack the degrees of freedom to perform the Lack of Fit tests. Also, the majority of the design points in D-optimal minimal designs are on the boundary: vertices, edges, or faces of the design simplex. In This Paper, Extensions Of The D-Optimal Minimal Designs Are Developed For A General Mixture Model To Allow Additional Interior Points In The Design Space To Enable Prediction Of The Entire Response Surface Also a new strategy for adding multiple interior points for symmetric mixture models is proposed. We compare the proposed designs with Cornell (1986) two ten-point designs for the Lack of Fit test by simulations. PMID:29081574

Monitoring of biopile composting of oily sludge.

PubMed

Kriipsalu, Mait; Nammari, Diauddin

2010-05-01

This paper describes a bioreactor set-up used to simulate degradation of petroleum hydrocarbons in a static biopile. The large-scale test was performed in a 28 m(3) custom-designed reactor. Oily sludge (40% by weight, having 7% dry matter [DM], and hydrocarbons C(10)-C(40) 160,000 mg kg(-1) DM) was mixed with organic-rich amendments - mature oil-compost (40%) and garden waste compost (20%). Within the reactor, the temperature and soil gases were monitored continuously during 370 days via 24 measurement points. Also, moisture content was continuously recorded and airflow through compost mix occasionally measured. Three-dimensional ordinary kriging spatial models were created to describe the dynamic variations of temperature, air distribution, and hydrocarbon concentration. There were large temperature differences in horizontal and vertical sections during initial months of composting only. Water content of the mixture was uneven by layers, referring on relocation of moisture due to aeration and condensation. The air distribution through the whole reactor varied largely despite of continuous aeration, while the concentration of O(2) was never reduced less than 1-2% on average. The results showed that composting of sludge using force-aerated static biopile technology was justified during the first 3-4 months, after which the masses could be re-mixed and heaped for further maturation in low-tech compost windrows. After 370 days of treatment, the content of hydrocarbons (C( 10)-C(40)) in the compost mixture was reduced by 68.7%.

Mercury-free dissolution of aluminum-clad fuel in nitric acid

DOEpatents

Christian, Jerry D.; Anderson, Philip A.

1994-01-01

A mercury-free dissolution process for aluminum involves placing the aluminum in a dissolver vessel in contact with nitric acid-fluoboric acid mixture at an elevated temperature. By maintaining a continuous flow of the acid mixture through the dissolver vessel, an effluent containing aluminum nitrate, nitric acid, fluoboric acid and other dissolved components are removed.

Mercury-free dissolution of aluminum-clad fuel in nitric acid

DOEpatents

Christian, J.D.; Anderson, P.A.

1994-11-15

A mercury-free dissolution process for aluminum involves placing the aluminum in a dissolver vessel in contact with nitric acid-fluoboric acid mixture at an elevated temperature. By maintaining a continuous flow of the acid mixture through the dissolver vessel, an effluent containing aluminum nitrate, nitric acid, fluoboric acid and other dissolved components are removed. 5 figs.

Fuel cell integrated with steam reformer

DOEpatents

Beshty, Bahjat S.; Whelan, James A.

1987-01-01

A H.sub.2 -air fuel cell integrated with a steam reformer is disclosed wherein a superheated water/methanol mixture is fed to a catalytic reformer to provide a continuous supply of hydrogen to the fuel cell, the gases exhausted from the anode of the fuel cell providing the thermal energy, via combustion, for superheating the water/methanol mixture.

40 CFR 355.13 - How do I calculate the quantity of an extremely hazardous substance present in mixtures?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 28 2011-07-01 2011-07-01 false How do I calculate the quantity of an extremely hazardous substance present in mixtures? 355.13 Section 355.13 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SUPERFUND, EMERGENCY PLANNING, AND COMMUNITY RIGHT-TO-KNOW PROGRAMS...

New approach in direct-simulation of gas mixtures

NASA Technical Reports Server (NTRS)

Chung, Chan-Hong; De Witt, Kenneth J.; Jeng, Duen-Ren

1991-01-01

Results are reported for an investigation of a new direct-simulation Monte Carlo method by which energy transfer and chemical reactions are calculated. The new method, which reduces to the variable cross-section hard sphere model as a special case, allows different viscosity-temperature exponents for each species in a gas mixture when combined with a modified Larsen-Borgnakke phenomenological model. This removes the most serious limitation of the usefulness of the model for engineering simulations. The necessary kinetic theory for the application of the new method to mixtures of monatomic or polyatomic gases is presented, including gas mixtures involving chemical reactions. Calculations are made for the relaxation of a diatomic gas mixture, a plane shock wave in a gas mixture, and a chemically reacting gas flow along the stagnation streamline in front of a hypersonic vehicle. Calculated results show that the introduction of different molecular interactions for each species in a gas mixture produces significant differences in comparison with a common molecular interaction for all species in the mixture. This effect should not be neglected for accurate DSMC simulations in an engineering context.

Investigation of Dalton and Amagat's laws for gas mixtures with shock propagation

NASA Astrophysics Data System (ADS)

Wayne, Patrick; Trueba Monje, Ignacio; Yoo, Jason H.; Truman, C. Randall; Vorobieff, Peter

2016-11-01

Two common models describing gas mixtures are Dalton's Law and Amagat's Law (also known as the laws of partial pressures and partial volumes, respectively). Our work is focused on determining the suitability of these models to prediction of effects of shock propagation through gas mixtures. Experiments are conducted at the Shock Tube Facility at the University of New Mexico (UNM). To validate experimental data, possible sources of uncertainty associated with experimental setup are identified and analyzed. The gaseous mixture of interest consists of a prescribed combination of disparate gases - helium and sulfur hexafluoride (SF6). The equations of state (EOS) considered are the ideal gas EOS for helium, and a virial EOS for SF6. The values for the properties provided by these EOS are then used used to model shock propagation through the mixture in accordance with Dalton's and Amagat's laws. Results of the modeling are compared with experiment to determine which law produces better agreement for the mixture. This work is funded by NNSA Grant DE-NA0002913.

Bayesian 2-Stage Space-Time Mixture Modeling With Spatial Misalignment of the Exposure in Small Area Health Data.

PubMed

Lawson, Andrew B; Choi, Jungsoon; Cai, Bo; Hossain, Monir; Kirby, Russell S; Liu, Jihong

2012-09-01

We develop a new Bayesian two-stage space-time mixture model to investigate the effects of air pollution on asthma. The two-stage mixture model proposed allows for the identification of temporal latent structure as well as the estimation of the effects of covariates on health outcomes. In the paper, we also consider spatial misalignment of exposure and health data. A simulation study is conducted to assess the performance of the 2-stage mixture model. We apply our statistical framework to a county-level ambulatory care asthma data set in the US state of Georgia for the years 1999-2008.

Subjective Prior Distributions for Modeling Longitudinal Continuous Outcomes with Non-Ignorable Dropout

PubMed Central

Paddock, Susan M.; Ebener, Patricia

2010-01-01

Substance abuse treatment research is complicated by the pervasive problem of non-ignorable missing data – i.e., the occurrence of the missing data is related to the unobserved outcomes. Missing data frequently arise due to early client departure from treatment. Pattern-mixture models (PMMs) are often employed in such situations to jointly model the outcome and the missing data mechanism. PMMs require non-testable assumptions to identify model parameters. Several approaches to parameter identification have therefore been explored for longitudinal modeling of continuous outcomes, and informative priors have been developed in other contexts. In this paper, we describe an expert interview conducted with five substance abuse treatment clinical experts who have familiarity with the Therapeutic Community modality of substance abuse treatment and with treatment process scores collected using the Dimensions of Change Instrument. The goal of the interviews was to obtain expert opinion about the rate of change in continuous client-level treatment process scores for clients who leave before completing two assessments and whose rate of change (slope) in treatment process scores is unidentified by the data. We find that the experts’ opinions differed dramatically from widely-utilized assumptions used to identify parameters in the PMM. Further, subjective prior assessment allows one to properly address the uncertainty inherent in the subjective decisions required to identify parameters in the PMM and to measure their effect on conclusions drawn from the analysis. PMID:19012279

Factorial Design Approach in Proportioning Prestressed Self-Compacting Concrete.

PubMed

Long, Wu-Jian; Khayat, Kamal Henri; Lemieux, Guillaume; Xing, Feng; Wang, Wei-Lun

2015-03-13

In order to model the effect of mixture parameters and material properties on the hardened properties of, prestressed self-compacting concrete (SCC), and also to investigate the extensions of the statistical models, a factorial design was employed to identify the relative significance of these primary parameters and their interactions in terms of the mechanical and visco-elastic properties of SCC. In addition to the 16 fractional factorial mixtures evaluated in the modeled region of -1 to +1, eight axial mixtures were prepared at extreme values of -2 and +2 with the other variables maintained at the central points. Four replicate central mixtures were also evaluated. The effects of five mixture parameters, including binder type, binder content, dosage of viscosity-modifying admixture (VMA), water-cementitious material ratio (w/cm), and sand-to-total aggregate ratio (S/A) on compressive strength, modulus of elasticity, as well as autogenous and drying shrinkage are discussed. The applications of the models to better understand trade-offs between mixture parameters and carry out comparisons among various responses are also highlighted. A logical design approach would be to use the existing model to predict the optimal design, and then run selected tests to quantify the influence of the new binder on the model.

Some comments on thermodynamic consistency for equilibrium mixture equations of state

DOE PAGES

Grove, John W.

2018-03-28

We investigate sufficient conditions for thermodynamic consistency for equilibrium mixtures. Such models assume that the mass fraction average of the material component equations of state, when closed by a suitable equilibrium condition, provide a composite equation of state for the mixture. Here, we show that the two common equilibrium models of component pressure/temperature equilibrium and volume/temperature equilibrium (Dalton, 1808) define thermodynamically consistent mixture equations of state and that other equilibrium conditions can be thermodynamically consistent provided appropriate values are used for the mixture specific entropy and pressure.

An On-Line Acoustic Fluorocarbon Coolant Mixture Analyzer for the ATLAS Silicon Tracker

NASA Astrophysics Data System (ADS)

Bates, R.; Battistin, M.; Berry, S.; Bitadze, A.; Bonneau, P.; Bousson, N.; Boyd, G.; Botelho-Direito, J.; DiGirolamo, B.; Doubek, M.; Egorov, K.; Godlewski, J.; Hallewell, G.; Katunin, S.; Mathieu, M.; McMahon, S.; Nagai, K.; Perez-Rodriguez, E.; Rozanov, A.; Vacek, V.; Vitek, M.

2012-10-01

The ATLAS silicon tracker community foresees an upgrade from the present octafluoropropane (C3F8) evaporative cooling fluid to a composite fluid with a probable 10-20% admixture of hexafluoroethane (C2F6). Such a fluid will allow a lower evaporation temperature and will afford the tracker silicon substrates a better safety margin against leakage current-induced thermal runaway caused by cumulative radiation damage as the luminosity profile at the CERN Large Hadron Collider increases. Central to the use of this new fluid is a new custom-developed speed-of-sound instrument for continuous real-time measurement of the C3F8/C2F6 mixture ratio and flow. An acoustic vapour mixture analyzer/flow meter with new custom electronics allowing ultrasonic frequency transmission through gas mixtures has been developed for this application. Synchronous with the emission of an ultrasound `chirp' from an acoustic transmitter, a fast readout clock (40 MHz) is started. The clock is stopped on receipt of an above threshold sound pulse at the receiver. Sound is alternately transmitted parallel and anti-parallel with the vapour flow for volume flow measurement from transducers that can serve as acoustic transmitters or receivers. In the development version, continuous real-time measurement of C3F8/C2F6 flow and calculation of the mixture ratio is performed within a graphical user interface developed in PVSS-II, the Supervisory, Control and Data Acquisition standard chosen for LHC and its experiments at CERN. The described instrument has numerous potential applications - including refrigerant leak detection, the analysis of hydrocarbons, vapour mixtures for semi-conductor manufacture and anesthetic gas mixtures.

Mixtures of amino-acid based ionic liquids and water.

PubMed

Chaban, Vitaly V; Fileti, Eudes Eterno

2015-09-01

New ionic liquids (ILs) involving increasing numbers of organic and inorganic ions are continuously being reported. We recently developed a new force field; in the present work, we applied that force field to investigate the structural properties of a few novel imidazolium-based ILs in aqueous mixtures via molecular dynamics (MD) simulations. Using cluster analysis, radial distribution functions, and spatial distribution functions, we argue that organic ions (imidazolium, deprotonated alanine, deprotonated methionine, deprotonated tryptophan) are well dispersed in aqueous media, irrespective of the IL content. Aqueous dispersions exhibit desirable properties for chemical engineering. The ILs exist as ion pairs in relatively dilute aqueous mixtures (10 mol%), while more concentrated mixtures feature a certain amount of larger ionic aggregates.

Continued Monitoring of Indiana's SPS9-A Site

DOT National Transportation Integrated Search

2012-07-01

This study was initiated to continue monitoring the performance of five test sections placed in 1997 to compare the performance of : Superpave asphalt mixtures with different binder grades and one test section designed using the Marshall mix design m...

Robust Bayesian clustering.

PubMed

Archambeau, Cédric; Verleysen, Michel

2007-01-01

A new variational Bayesian learning algorithm for Student-t mixture models is introduced. This algorithm leads to (i) robust density estimation, (ii) robust clustering and (iii) robust automatic model selection. Gaussian mixture models are learning machines which are based on a divide-and-conquer approach. They are commonly used for density estimation and clustering tasks, but are sensitive to outliers. The Student-t distribution has heavier tails than the Gaussian distribution and is therefore less sensitive to any departure of the empirical distribution from Gaussianity. As a consequence, the Student-t distribution is suitable for constructing robust mixture models. In this work, we formalize the Bayesian Student-t mixture model as a latent variable model in a different way from Svensén and Bishop [Svensén, M., & Bishop, C. M. (2005). Robust Bayesian mixture modelling. Neurocomputing, 64, 235-252]. The main difference resides in the fact that it is not necessary to assume a factorized approximation of the posterior distribution on the latent indicator variables and the latent scale variables in order to obtain a tractable solution. Not neglecting the correlations between these unobserved random variables leads to a Bayesian model having an increased robustness. Furthermore, it is expected that the lower bound on the log-evidence is tighter. Based on this bound, the model complexity, i.e. the number of components in the mixture, can be inferred with a higher confidence.

A quantitative trait locus mixture model that avoids spurious LOD score peaks.

PubMed Central

Feenstra, Bjarke; Skovgaard, Ib M

2004-01-01

In standard interval mapping of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. At any given location in the genome, the evidence of a putative QTL is measured by the likelihood ratio of the mixture model compared to a single normal distribution (the LOD score). This approach can occasionally produce spurious LOD score peaks in regions of low genotype information (e.g., widely spaced markers), especially if the phenotype distribution deviates markedly from a normal distribution. Such peaks are not indicative of a QTL effect; rather, they are caused by the fact that a mixture of normals always produces a better fit than a single normal distribution. In this study, a mixture model for QTL mapping that avoids the problems of such spurious LOD score peaks is presented. PMID:15238544

A quantitative trait locus mixture model that avoids spurious LOD score peaks.

PubMed

Feenstra, Bjarke; Skovgaard, Ib M

2004-06-01

In standard interval mapping of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. At any given location in the genome, the evidence of a putative QTL is measured by the likelihood ratio of the mixture model compared to a single normal distribution (the LOD score). This approach can occasionally produce spurious LOD score peaks in regions of low genotype information (e.g., widely spaced markers), especially if the phenotype distribution deviates markedly from a normal distribution. Such peaks are not indicative of a QTL effect; rather, they are caused by the fact that a mixture of normals always produces a better fit than a single normal distribution. In this study, a mixture model for QTL mapping that avoids the problems of such spurious LOD score peaks is presented.

Extensions of D-optimal Minimal Designs for Symmetric Mixture Models.

PubMed

Li, Yanyan; Raghavarao, Damaraju; Chervoneva, Inna

2017-01-01

The purpose of mixture experiments is to explore the optimum blends of mixture components, which will provide desirable response characteristics in finished products. D-optimal minimal designs have been considered for a variety of mixture models, including Scheffé's linear, quadratic, and cubic models. Usually, these D-optimal designs are minimally supported since they have just as many design points as the number of parameters. Thus, they lack the degrees of freedom to perform the Lack of Fit tests. Also, the majority of the design points in D-optimal minimal designs are on the boundary: vertices, edges, or faces of the design simplex. Also a new strategy for adding multiple interior points for symmetric mixture models is proposed. We compare the proposed designs with Cornell (1986) two ten-point designs for the Lack of Fit test by simulations.

Temporal properties of secondary drop breakup in the bag-stamen breakup regime

NASA Astrophysics Data System (ADS)

Zhao, Hui; Liu, Hai-Feng; Xu, Jian-Liang; Li, Wei-Feng; Lin, Kuang-Fei

2013-05-01

The situation of liquid drop bag-stamen breakup in a continuous air jet flow is investigated by a high speed camera. Test liquids include water, ethanol, and various glycerol mixtures. First, the morphology of bag-stamen breakup is observed and analyzed. The bag-stamen breakup range is found to be in good agreement with the model obtained by Rayleigh-Taylor instability. Then the disk and stamen deformation properties, the fragment average size, and size distribution of ring and stamen are researched in detail, respectively.

Mixture of autoregressive modeling orders and its implication on single trial EEG classification

PubMed Central

Atyabi, Adham; Shic, Frederick; Naples, Adam

2016-01-01

Autoregressive (AR) models are of commonly utilized feature types in Electroencephalogram (EEG) studies due to offering better resolution, smoother spectra and being applicable to short segments of data. Identifying correct AR’s modeling order is an open challenge. Lower model orders poorly represent the signal while higher orders increase noise. Conventional methods for estimating modeling order includes Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Final Prediction Error (FPE). This article assesses the hypothesis that appropriate mixture of multiple AR orders is likely to better represent the true signal compared to any single order. Better spectral representation of underlying EEG patterns can increase utility of AR features in Brain Computer Interface (BCI) systems by increasing timely & correctly responsiveness of such systems to operator’s thoughts. Two mechanisms of Evolutionary-based fusion and Ensemble-based mixture are utilized for identifying such appropriate mixture of modeling orders. The classification performance of the resultant AR-mixtures are assessed against several conventional methods utilized by the community including 1) A well-known set of commonly used orders suggested by the literature, 2) conventional order estimation approaches (e.g., AIC, BIC and FPE), 3) blind mixture of AR features originated from a range of well-known orders. Five datasets from BCI competition III that contain 2, 3 and 4 motor imagery tasks are considered for the assessment. The results indicate superiority of Ensemble-based modeling order mixture and evolutionary-based order fusion methods within all datasets. PMID:28740331

The structure of evaporating and combusting sprays: Measurements and predictions

NASA Technical Reports Server (NTRS)

Shuen, J. S.; Solomon, A. S. P.; Faeth, F. M.

1983-01-01

The structure of particle-laden jets and nonevaporating and evaporating sprays was measured in order to evaluate models of these processes. Three models are being evaluated: (1) a locally homogeneous flow model, where slip between the phases is neglected and the flow is assumed to be in local thermodynamic equilibrium; (2) a deterministic separated flow model, where slip and finite interphase transport rates are considered but effects of particle/drop dispersion by turbulence and effects of turbulence on interphase transport rates are ignored; and (3) a stochastic separated flow model, where effects of interphase slip, turbulent dispersion and turbulent fluctuations are considered using random sampling for turbulence properties in conjunction with random-walk computations for particle motion. All three models use a k-e-g turbulence model. All testing and data reduction are completed for the particle laden jets. Mean and fluctuating velocities of the continuous phase and mean mixture fraction were measured in the evaporating sprays.

Bayesian analysis of Jolly-Seber type models

USGS Publications Warehouse

Matechou, Eleni; Nicholls, Geoff K.; Morgan, Byron J. T.; Collazo, Jaime A.; Lyons, James E.

2016-01-01

We propose the use of finite mixtures of continuous distributions in modelling the process by which new individuals, that arrive in groups, become part of a wildlife population. We demonstrate this approach using a data set of migrating semipalmated sandpipers (Calidris pussila) for which we extend existing stopover models to allow for individuals to have different behaviour in terms of their stopover duration at the site. We demonstrate the use of reversible jump MCMC methods to derive posterior distributions for the model parameters and the models, simultaneously. The algorithm moves between models with different numbers of arrival groups as well as between models with different numbers of behavioural groups. The approach is shown to provide new ecological insights about the stopover behaviour of semipalmated sandpipers but is generally applicable to any population in which animals arrive in groups and potentially exhibit heterogeneity in terms of one or more other processes.

Single- and mixture toxicity of three organic UV-filters, ethylhexyl methoxycinnamate, octocrylene, and avobenzone on Daphnia magna.

PubMed

Park, Chang-Beom; Jang, Jiyi; Kim, Sanghun; Kim, Young Jun

2017-03-01

In freshwater environments, aquatic organisms are generally exposed to mixtures of various chemical substances. In this study, we tested the toxicity of three organic UV-filters (ethylhexyl methoxycinnamate, octocrylene, and avobenzone) to Daphnia magna in order to evaluate the combined toxicity of these substances when in they occur in a mixture. The values of effective concentrations (ECx) for each UV-filter were calculated by concentration-response curves; concentration-combinations of three different UV-filters in a mixture were determined by the fraction of components based on EC 25 values predicted by concentration addition (CA) model. The interaction between the UV-filters were also assessed by model deviation ratio (MDR) using observed and predicted toxicity values obtained from mixture-exposure tests and CA model. The results from this study indicated that observed ECx mix (e.g., EC 10mix , EC 25mix , or EC 50mix ) values obtained from mixture-exposure tests were higher than predicted ECx mix (e.g., EC 10mix , EC 25mix , or EC 50mix ) values calculated by CA model. MDR values were also less than a factor of 1.0 in a mixtures of three different UV-filters. Based on these results, we suggest for the first time a reduction of toxic effects in the mixtures of three UV-filters, caused by antagonistic action of the components. Our findings from this study will provide important information for hazard or risk assessment of organic UV-filters, when they existed together in the aquatic environment. To better understand the mixture toxicity and the interaction of components in a mixture, further studies for various combinations of mixture components are also required. Copyright © 2016 Elsevier Inc. All rights reserved.

Linking asphalt binder fatigue to asphalt mixture fatigue performance using viscoelastic continuum damage modeling

NASA Astrophysics Data System (ADS)

Safaei, Farinaz; Castorena, Cassie; Kim, Y. Richard

2016-08-01

Fatigue cracking is a major form of distress in asphalt pavements. Asphalt binder is the weakest asphalt concrete constituent and, thus, plays a critical role in determining the fatigue resistance of pavements. Therefore, the ability to characterize and model the inherent fatigue performance of an asphalt binder is a necessary first step to design mixtures and pavements that are not susceptible to premature fatigue failure. The simplified viscoelastic continuum damage (S-VECD) model has been used successfully by researchers to predict the damage evolution in asphalt mixtures for various traffic and climatic conditions using limited uniaxial test data. In this study, the S-VECD model, developed for asphalt mixtures, is adapted for asphalt binders tested under cyclic torsion in a dynamic shear rheometer. Derivation of the model framework is presented. The model is verified by producing damage characteristic curves that are both temperature- and loading history-independent based on time sweep tests, given that the effects of plasticity and adhesion loss on the material behavior are minimal. The applicability of the S-VECD model to the accelerated loading that is inherent of the linear amplitude sweep test is demonstrated, which reveals reasonable performance predictions, but with some loss in accuracy compared to time sweep tests due to the confounding effects of nonlinearity imposed by the high strain amplitudes included in the test. The asphalt binder S-VECD model is validated through comparisons to asphalt mixture S-VECD model results derived from cyclic direct tension tests and Accelerated Loading Facility performance tests. The results demonstrate good agreement between the asphalt binder and mixture test results and pavement performance, indicating that the developed model framework is able to capture the asphalt binder's contribution to mixture fatigue and pavement fatigue cracking performance.

Cumulative toxicity of neonicotinoid insecticide mixtures to Chironomus dilutus under acute exposure scenarios.

PubMed

Maloney, Erin M; Morrissey, Christy A; Headley, John V; Peru, Kerry M; Liber, Karsten

2017-11-01

Extensive agricultural use of neonicotinoid insecticide products has resulted in the presence of neonicotinoid mixtures in surface waters worldwide. Although many aquatic insect species are known to be sensitive to neonicotinoids, the impact of neonicotinoid mixtures is poorly understood. In the present study, the cumulative toxicities of binary and ternary mixtures of select neonicotinoids (imidacloprid, clothianidin, and thiamethoxam) were characterized under acute (96-h) exposure scenarios using the larval midge Chironomus dilutus as a representative aquatic insect species. Using the MIXTOX approach, predictive parametric models were fitted and statistically compared with observed toxicity in subsequent mixture tests. Single-compound toxicity tests yielded median lethal concentration (LC50) values of 4.63, 5.93, and 55.34 μg/L for imidacloprid, clothianidin, and thiamethoxam, respectively. Because of the similar modes of action of neonicotinoids, concentration-additive cumulative mixture toxicity was the predicted model. However, we found that imidacloprid-clothianidin mixtures demonstrated response-additive dose-level-dependent synergism, clothianidin-thiamethoxam mixtures demonstrated concentration-additive synergism, and imidacloprid-thiamethoxam mixtures demonstrated response-additive dose-ratio-dependent synergism, with toxicity shifting from antagonism to synergism as the relative concentration of thiamethoxam increased. Imidacloprid-clothianidin-thiamethoxam ternary mixtures demonstrated response-additive synergism. These results indicate that, under acute exposure scenarios, the toxicity of neonicotinoid mixtures to C. dilutus cannot be predicted using the common assumption of additive joint activity. Indeed, the overarching trend of synergistic deviation emphasizes the need for further research into the ecotoxicological effects of neonicotinoid insecticide mixtures in field settings, the development of better toxicity models for neonicotinoid mixture exposures, and the consideration of mixture effects when setting water quality guidelines for this class of pesticides. Environ Toxicol Chem 2017;36:3091-3101. © 2017 SETAC. © 2017 SETAC.

Mixture modeling methods for the assessment of normal and abnormal personality, part II: longitudinal models.

PubMed

Wright, Aidan G C; Hallquist, Michael N

2014-01-01

Studying personality and its pathology as it changes, develops, or remains stable over time offers exciting insight into the nature of individual differences. Researchers interested in examining personal characteristics over time have a number of time-honored analytic approaches at their disposal. In recent years there have also been considerable advances in person-oriented analytic approaches, particularly longitudinal mixture models. In this methodological primer we focus on mixture modeling approaches to the study of normative and individual change in the form of growth mixture models and ipsative change in the form of latent transition analysis. We describe the conceptual underpinnings of each of these models, outline approaches for their implementation, and provide accessible examples for researchers studying personality and its assessment.

Numerical simulation of asphalt mixtures fracture using continuum models

NASA Astrophysics Data System (ADS)

Szydłowski, Cezary; Górski, Jarosław; Stienss, Marcin; Smakosz, Łukasz

2018-01-01

The paper considers numerical models of fracture processes of semi-circular asphalt mixture specimens subjected to three-point bending. Parameter calibration of the asphalt mixture constitutive models requires advanced, complex experimental test procedures. The highly non-homogeneous material is numerically modelled by a quasi-continuum model. The computational parameters are averaged data of the components, i.e. asphalt, aggregate and the air voids composing the material. The model directly captures random nature of material parameters and aggregate distribution in specimens. Initial results of the analysis are presented here.

Introduction to the special section on mixture modeling in personality assessment.

PubMed

Wright, Aidan G C; Hallquist, Michael N

2014-01-01

Latent variable models offer a conceptual and statistical framework for evaluating the underlying structure of psychological constructs, including personality and psychopathology. Complex structures that combine or compare categorical and dimensional latent variables can be accommodated using mixture modeling approaches, which provide a powerful framework for testing nuanced theories about psychological structure. This special series includes introductory primers on cross-sectional and longitudinal mixture modeling, in addition to empirical examples applying these techniques to real-world data collected in clinical settings. This group of articles is designed to introduce personality assessment scientists and practitioners to a general latent variable framework that we hope will stimulate new research and application of mixture models to the assessment of personality and its pathology.

Predicting the shock compression response of heterogeneous powder mixtures

NASA Astrophysics Data System (ADS)

Fredenburg, D. A.; Thadhani, N. N.

2013-06-01

A model framework for predicting the dynamic shock-compression response of heterogeneous powder mixtures using readily obtained measurements from quasi-static tests is presented. Low-strain-rate compression data are first analyzed to determine the region of the bulk response over which particle rearrangement does not contribute to compaction. This region is then fit to determine the densification modulus of the mixture, σD, an newly defined parameter describing the resistance of the mixture to yielding. The measured densification modulus, reflective of the diverse yielding phenomena that occur at the meso-scale, is implemented into a rate-independent formulation of the P-α model, which is combined with an isobaric equation of state to predict the low and high stress dynamic compression response of heterogeneous powder mixtures. The framework is applied to two metal + metal-oxide (thermite) powder mixtures, and good agreement between the model and experiment is obtained for all mixtures at stresses near and above those required to reach full density. At lower stresses, rate-dependencies of the constituents, and specifically those of the matrix constituent, determine the ability of the model to predict the measured response in the incomplete compaction regime.

Continuous-Flow Production of Injectable Liposomes via a Microfluidic Approach

PubMed Central

Zizzari, Alessandra; Bianco, Monica; Perrone, Elisabetta; Amato, Francesco; Maruccio, Giuseppe; Rendina, Filippo; Arima, Valentina

2017-01-01

Injectable liposomes are characterized by a suitable size and unique lipid mixtures, which require time-consuming and nonstraightforward production processes. The complexity of the manufacturing methods may affect liposome solubility, the phase transition temperatures of the membranes, the average particle size, and the associated particle size distribution, with a possible impact on the drug encapsulation and release. By leveraging the precise steady-state control over the mixing of miscible liquids and a highly efficient heat transfer, microfluidic technology has proved to be an effective and direct methodology to produce liposomes. This approach results particularly efficient in reducing the number of the sizing steps, when compared to standard industrial methods. Here, Microfluidic Hydrodynamic Focusing chips were produced and used to form liposomes upon tuning experimental parameters such as lipids concentration and Flow-Rate-Ratios (FRRs). Although modelling evidenced the dependence of the laminar flow on the geometric constraints and the FRR conditions, for the specific formulation investigated in this study, the lipids concentration was identified as the primary factor influencing the size of the liposomes and their polydispersity index. This was attributed to a predominance of the bending elasticity modulus over the vesiculation index in the lipid mixture used. Eventually, liposomes of injectable size were produced using microfluidic one-pot synthesis in continuous flow. PMID:29232873

Anomaly detection of microstructural defects in continuous fiber reinforced composites

NASA Astrophysics Data System (ADS)

Bricker, Stephen; Simmons, J. P.; Przybyla, Craig; Hardie, Russell

2015-03-01

Ceramic matrix composites (CMC) with continuous fiber reinforcements have the potential to enable the next generation of high speed hypersonic vehicles and/or significant improvements in gas turbine engine performance due to their exhibited toughness when subjected to high mechanical loads at extreme temperatures (2200F+). Reinforced fiber composites (RFC) provide increased fracture toughness, crack growth resistance, and strength, though little is known about how stochastic variation and imperfections in the material effect material properties. In this work, tools are developed for quantifying anomalies within the microstructure at several scales. The detection and characterization of anomalous microstructure is a critical step in linking production techniques to properties, as well as in accurate material simulation and property prediction for the integrated computation materials engineering (ICME) of RFC based components. It is desired to find statistical outliers for any number of material characteristics such as fibers, fiber coatings, and pores. Here, fiber orientation, or `velocity', and `velocity' gradient are developed and examined for anomalous behavior. Categorizing anomalous behavior in the CMC is approached by multivariate Gaussian mixture modeling. A Gaussian mixture is employed to estimate the probability density function (PDF) of the features in question, and anomalies are classified by their likelihood of belonging to the statistical normal behavior for that feature.

D-optimal experimental designs to test for departure from additivity in a fixed-ratio mixture ray.

PubMed

Coffey, Todd; Gennings, Chris; Simmons, Jane Ellen; Herr, David W

2005-12-01

Traditional factorial designs for evaluating interactions among chemicals in a mixture may be prohibitive when the number of chemicals is large. Using a mixture of chemicals with a fixed ratio (mixture ray) results in an economical design that allows estimation of additivity or nonadditive interaction for a mixture of interest. This methodology is extended easily to a mixture with a large number of chemicals. Optimal experimental conditions can be chosen that result in increased power to detect departures from additivity. Although these designs are used widely for linear models, optimal designs for nonlinear threshold models are less well known. In the present work, the use of D-optimal designs is demonstrated for nonlinear threshold models applied to a fixed-ratio mixture ray. For a fixed sample size, this design criterion selects the experimental doses and number of subjects per dose level that result in minimum variance of the model parameters and thus increased power to detect departures from additivity. An optimal design is illustrated for a 2:1 ratio (chlorpyrifos:carbaryl) mixture experiment. For this example, and in general, the optimal designs for the nonlinear threshold model depend on prior specification of the slope and dose threshold parameters. Use of a D-optimal criterion produces experimental designs with increased power, whereas standard nonoptimal designs with equally spaced dose groups may result in low power if the active range or threshold is missed.

Gravel-Sand-Clay Mixture Model for Predictions of Permeability and Velocity of Unconsolidated Sediments

NASA Astrophysics Data System (ADS)

Konishi, C.

2014-12-01

Gravel-sand-clay mixture model is proposed particularly for unconsolidated sediments to predict permeability and velocity from volume fractions of the three components (i.e. gravel, sand, and clay). A well-known sand-clay mixture model or bimodal mixture model treats clay contents as volume fraction of the small particle and the rest of the volume is considered as that of the large particle. This simple approach has been commonly accepted and has validated by many studies before. However, a collection of laboratory measurements of permeability and grain size distribution for unconsolidated samples show an impact of presence of another large particle; i.e. only a few percent of gravel particles increases the permeability of the sample significantly. This observation cannot be explained by the bimodal mixture model and it suggests the necessity of considering the gravel-sand-clay mixture model. In the proposed model, I consider the three volume fractions of each component instead of using only the clay contents. Sand becomes either larger or smaller particles in the three component mixture model, whereas it is always the large particle in the bimodal mixture model. The total porosity of the two cases, one is the case that the sand is smaller particle and the other is the case that the sand is larger particle, can be modeled independently from sand volume fraction by the same fashion in the bimodal model. However, the two cases can co-exist in one sample; thus, the total porosity of the mixed sample is calculated by weighted average of the two cases by the volume fractions of gravel and clay. The effective porosity is distinguished from the total porosity assuming that the porosity associated with clay is zero effective porosity. In addition, effective grain size can be computed from the volume fractions and representative grain sizes for each component. Using the effective porosity and the effective grain size, the permeability is predicted by Kozeny-Carman equation. Furthermore, elastic properties are obtainable by general Hashin-Shtrikman-Walpole bounds. The predicted results by this new mixture model are qualitatively consistent with laboratory measurements and well log obtained for unconsolidated sediments. Acknowledgement: A part of this study was accomplished with a subsidy of River Environment Fund of Japan.

A numerical study of granular dam-break flow

NASA Astrophysics Data System (ADS)

Pophet, N.; Rébillout, L.; Ozeren, Y.; Altinakar, M.

2017-12-01

Accurate prediction of granular flow behavior is essential to optimize mitigation measures for hazardous natural granular flows such as landslides, debris flows and tailings-dam break flows. So far, most successful models for these types of flows focus on either pure granular flows or flows of saturated grain-fluid mixtures by employing a constant friction model or more complex rheological models. These saturated models often produce non-physical result when they are applied to simulate flows of partially saturated mixtures. Therefore, more advanced models are needed. A numerical model was developed for granular flow employing a constant friction and μ(I) rheology (Jop et al., J. Fluid Mech. 2005) coupled with a groundwater flow model for seepage flow. The granular flow is simulated by solving a mixture model using Finite Volume Method (FVM). The Volume-of-Fluid (VOF) technique is used to capture the free surface motion. The constant friction and μ(I) rheological models are incorporated in the mixture model. The seepage flow is modeled by solving Richards equation. A framework is developed to couple these two solvers in OpenFOAM. The model was validated and tested by reproducing laboratory experiments of partially and fully channelized dam-break flows of dry and initially saturated granular material. To obtain appropriate parameters for rheological models, a series of simulations with different sets of rheological parameters is performed. The simulation results obtained from constant friction and μ(I) rheological models are compared with laboratory experiments for granular free surface interface, front position and velocity field during the flows. The numerical predictions indicate that the proposed model is promising in predicting dynamics of the flow and deposition process. The proposed model may provide more reliable insight than the previous assumed saturated mixture model, when saturated and partially saturated portions of granular mixture co-exist.

Quantifying Grassland-to-Woodland Transitions and the Implications for Carbon and Nitrogen Dynamics in the Southwest United States

NASA Technical Reports Server (NTRS)

Wessman, Carol A.; Archer, Steven R.; Asner, Gregory P.; Bateson, C. Ann

2004-01-01

Replacement of grasslands and savannas by shrublands and woodlands has been widely reported in tropical, temperate and high-latitude rangelands worldwide (Archer 1994). These changes in vegetation structure may reflect historical shifts in climate and land use; and are likely to influence biodiversity, productivity, above- and below ground carbon and nitrogen sequestration and biophysical aspects of land surface-atmosphere interactions. The goal of our proposed research is to investigate how changes in the relative abundance of herbaceous and woody vegetation affect carbon and nitrogen dynamics across heterogeneous savannas and shrub/woodlands. By linking actual land-cover composition (derived through spectral mixture analysis of AVIRIS, TM, and AVHRR imagery) with a process-based ecosystem model, we will generate explicit predictions of the C and N storage in plants and soils resulting from changes in vegetation structure. Our specific objectives will be to (1) continue development and test applications of spectral mixture analysis across grassland-to-woodland transitions; (2) quantify temporal changes in plant and soil C and N storage and turnover for remote sensing and process model parameterization and verification; and (3) couple landscape fraction maps to an ecosystem simulation model to observe biogeochemical dynamics under changing landscape structure and climatological forcings.

Low Mach number fluctuating hydrodynamics for electrolytes

DOE PAGES

Péraud, Jean-Philippe; Nonaka, Andy; Chaudhri, Anuj; ...

2016-11-18

Here, we formulate and study computationally the low Mach number fluctuating hydrodynamic equations for electrolyte solutions. We are also interested in studying transport in mixtures of charged species at the mesoscale, down to scales below the Debye length, where thermal fluctuations have a significant impact on the dynamics. Continuing our previous work on fluctuating hydrodynamics of multicomponent mixtures of incompressible isothermal miscible liquids (A. Donev, et al., Physics of Fluids, 27, 3, 2015), we now include the effect of charged species using a quasielectrostatic approximation. Localized charges create an electric field, which in turn provides additional forcing in the massmore » and momentum equations. Our low Mach number formulation eliminates sound waves from the fully compressible formulation and leads to a more computationally efficient quasi-incompressible formulation. Furthermore, we demonstrate our ability to model saltwater (NaCl) solutions in both equilibrium and nonequilibrium settings. We show that our algorithm is second-order in the deterministic setting, and for length scales much greater than the Debye length gives results consistent with an electroneutral/ambipolar approximation. In the stochastic setting, our model captures the predicted dynamics of equilibrium and nonequilibrium fluctuations. We also identify and model an instability that appears when diffusive mixing occurs in the presence of an applied electric field.« less

Continuous automated sensing of streamflow density as a surrogate for suspended-sediment concentration sampling

USGS Publications Warehouse

Larsen, Matthew C.; Figueroa Alamo, Carlos; Gray, John R.; Fletcher, William

2001-01-01

A newly refined technique for continuously and automatically sensing the density of a water-sediment mixture is being tested at a U.S. Geological Survey streamflow-gaging station in Puerto Rico. Originally developed to measure crude oil density, the double bubbler instrument measures fluid density by means of pressure transducers at two elevations in a vertical water column. By subtracting the density of water from the value measured for the density of the water-sediment mixture, the concentration of suspended sediment can be estimated. Preliminary tests of the double bubbler instrument show promise but are not yet conclusive.

An easy-to-use calculating machine to simulate steady state and non-steady-state preparative separations by multiple dual mode counter-current chromatography with semi-continuous loading of feed mixtures.

PubMed

Kostanyan, Artak E; Shishilov, Oleg N

2018-06-01

Multiple dual mode counter-current chromatography (MDM CCC) separation processes with semi-continuous large sample loading consist of a succession of two counter-current steps: with "x" phase (first step) and "y" phase (second step) flow periods. A feed mixture dissolved in the "x" phase is continuously loaded into a CCC machine at the beginning of the first step of each cycle over a constant time with the volumetric rate equal to the flow rate of the pure "x" phase. An easy-to-use calculating machine is developed to simulate the chromatograms and the amounts of solutes eluted with the phases at each cycle for steady-state (the duration of the flow periods of the phases is kept constant for all the cycles) and non-steady-state (with variable duration of alternating phase elution steps) separations. Using the calculating machine, the separation of mixtures containing up to five components can be simulated and designed. Examples of the application of the calculating machine for the simulation of MDM CCC processes are discussed. Copyright © 2018 Elsevier B.V. All rights reserved.

Mixture theory-based poroelasticity as a model of interstitial tissue growth

PubMed Central

Cowin, Stephen C.; Cardoso, Luis

2011-01-01

This contribution presents an alternative approach to mixture theory-based poroelasticity by transferring some poroelastic concepts developed by Maurice Biot to mixture theory. These concepts are a larger RVE and the subRVE-RVE velocity average tensor, which Biot called the micro-macro velocity average tensor. This velocity average tensor is assumed here to depend upon the pore structure fabric. The formulation of mixture theory presented is directed toward the modeling of interstitial growth, that is to say changing mass and changing density of an organism. Traditional mixture theory considers constituents to be open systems, but the entire mixture is a closed system. In this development the mixture is also considered to be an open system as an alternative method of modeling growth. Growth is slow and accelerations are neglected in the applications. The velocity of a solid constituent is employed as the main reference velocity in preference to the mean velocity concept from the original formulation of mixture theory. The standard development of statements of the conservation principles and entropy inequality employed in mixture theory are modified to account for these kinematic changes and to allow for supplies of mass, momentum and energy to each constituent and to the mixture as a whole. The objective is to establish a basis for the development of constitutive equations for growth of tissues. PMID:22184481

Mixture theory-based poroelasticity as a model of interstitial tissue growth.

PubMed

Cowin, Stephen C; Cardoso, Luis

2012-01-01

This contribution presents an alternative approach to mixture theory-based poroelasticity by transferring some poroelastic concepts developed by Maurice Biot to mixture theory. These concepts are a larger RVE and the subRVE-RVE velocity average tensor, which Biot called the micro-macro velocity average tensor. This velocity average tensor is assumed here to depend upon the pore structure fabric. The formulation of mixture theory presented is directed toward the modeling of interstitial growth, that is to say changing mass and changing density of an organism. Traditional mixture theory considers constituents to be open systems, but the entire mixture is a closed system. In this development the mixture is also considered to be an open system as an alternative method of modeling growth. Growth is slow and accelerations are neglected in the applications. The velocity of a solid constituent is employed as the main reference velocity in preference to the mean velocity concept from the original formulation of mixture theory. The standard development of statements of the conservation principles and entropy inequality employed in mixture theory are modified to account for these kinematic changes and to allow for supplies of mass, momentum and energy to each constituent and to the mixture as a whole. The objective is to establish a basis for the development of constitutive equations for growth of tissues.

10 CFR 504.7 - Prohibition against excessive use of petroleum or natural gas in mixtures-electing powerplants.

Code of Federal Regulations, 2012 CFR

2012-01-01

... fuel as its primary energy source, OFP may prohibit, by order, the use in that unit of petroleum or... 10 Energy 4 2012-01-01 2012-01-01 false Prohibition against excessive use of petroleum or natural gas in mixtures-electing powerplants. 504.7 Section 504.7 Energy DEPARTMENT OF ENERGY (CONTINUED...

10 CFR 504.7 - Prohibition against excessive use of petroleum or natural gas in mixtures-electing powerplants.

Code of Federal Regulations, 2014 CFR

2014-01-01

... fuel as its primary energy source, OFP may prohibit, by order, the use in that unit of petroleum or... 10 Energy 4 2014-01-01 2014-01-01 false Prohibition against excessive use of petroleum or natural gas in mixtures-electing powerplants. 504.7 Section 504.7 Energy DEPARTMENT OF ENERGY (CONTINUED...

10 CFR 504.7 - Prohibition against excessive use of petroleum or natural gas in mixtures-electing powerplants.

Code of Federal Regulations, 2013 CFR

2013-01-01

... fuel as its primary energy source, OFP may prohibit, by order, the use in that unit of petroleum or... 10 Energy 4 2013-01-01 2013-01-01 false Prohibition against excessive use of petroleum or natural gas in mixtures-electing powerplants. 504.7 Section 504.7 Energy DEPARTMENT OF ENERGY (CONTINUED...

Navier-Stokes analysis of cold scramjet-afterbody flows

NASA Technical Reports Server (NTRS)

Baysal, Oktay; Engelund, Walter C.; Eleshaky, Mohamed E.

1989-01-01

The progress of two efforts in coding solutions of Navier-Stokes equations is summarized. The first effort concerns a 3-D space marching parabolized Navier-Stokes (PNS) code being modified to compute the supersonic mixing flow through an internal/external expansion nozzle with multicomponent gases. The 3-D PNS equations, coupled with a set of species continuity equations, are solved using an implicit finite difference scheme. The completed work is summarized and includes code modifications for four chemical species, computing the flow upstream of the upper cowl for a theoretical air mixture, developing an initial plane solution for the inner nozzle region, and computing the flow inside the nozzle for both a N2/O2 mixture and a Freon-12/Ar mixture, and plotting density-pressure contours for the inner nozzle region. The second effort concerns a full Navier-Stokes code. The species continuity equations account for the diffusion of multiple gases. This 3-D explicit afterbody code has the ability to use high order numerical integration schemes such as the 4th order MacCormack, and the Gottlieb-MacCormack schemes. Changes to the work are listed and include, but are not limited to: (1) internal/external flow capability; (2) new treatments of the cowl wall boundary conditions and relaxed computations around the cowl region and cowl tip; (3) the entering of the thermodynamic and transport properties of Freon-12, Ar, O, and N; (4) modification to the Baldwin-Lomax turbulence model to account for turbulent eddies generated by cowl walls inside and external to the nozzle; and (5) adopting a relaxation formula to account for the turbulence in the mixing shear layer.

Repeated subcutaneous administrations of krokodil causes skin necrosis and internal organs toxicity in Wistar rats: putative human implications.

PubMed

Alves, Emanuele Amorim; Brandão, Pedro; Neves, João Filipe; Cravo, Sara Manuela; Soares, José Xavier; Grund, Jean-Paul C; Duarte, José Alberto; Afonso, Carlos M M; Pereira Netto, Annibal Duarte; Carvalho, Félix; Dinis-Oliveira, Ricardo Jorge

2017-05-01

"Krokodil" is the street name for an impure homemade drug mixture used as a cheap substitute for heroin, containing desomorphine as the main opioid. Abscesses, gangrene, thrombophlebitis, limb ulceration and amputations, jaw osteonecrosis, skin discoloration, ulcers, skin infections, and bleeding are some of the typical reported signs in humans. This study aimed to understand the toxicity of krokodil using Wistar male rats as experimental model. Animals were divided into seven groups and exposed subcutaneously to NaCl 0.9% (control), krokodil mixture free of psychotropic substances (blank krokodil), pharmaceutical grade desomorphine 1 mg/kg, and four different concentrations of krokodil (containing 0.125, 0.25, 0.5, and 1 mg/kg of desomorphine) synthesized accordingly to a "domestic" protocol followed by people who inject krokodil (PWIK). Daily injections for five consecutive days were performed, and animals were sacrificed 24 hr after the last administration. Biochemical and histological analysis were carried out. It was shown that the continuous use of krokodil may cause injury at the injection area, with formation of necrotic zones. The biochemical results evidenced alterations on cardiac and renal biomarkers of toxicity, namely, creatine kinase, creatine kinase-MB, and uric acid. Significant alteration in levels of reduced and oxidized glutathione on kidney and heart suggested that oxidative stress may be involved in krokodil-mediated toxicity. Cardiac congestion was the most relevant finding of continuous krokodil administration. These findings contribute notably to comprehension of the local and systemic toxicological impact of this complex drug mixture on major organs and will hopefully be useful for the development of appropriate treatment strategies towards the human toxicological effects of krokodil. Copyright © 2017 John Wiley & Sons, Ltd.

Pairwise mixture model for unmixing partial volume effect in multi-voxel MR spectroscopy of brain tumour patients

NASA Astrophysics Data System (ADS)

Olliverre, Nathan; Asad, Muhammad; Yang, Guang; Howe, Franklyn; Slabaugh, Gregory

2017-03-01

Multi-Voxel Magnetic Resonance Spectroscopy (MV-MRS) provides an important and insightful technique for the examination of the chemical composition of brain tissue, making it an attractive medical imaging modality for the examination of brain tumours. MRS, however, is affected by the issue of the Partial Volume Effect (PVE), where the signals of multiple tissue types can be found within a single voxel and provides an obstacle to the interpretation of the data. The PVE results from the low resolution achieved in MV-MRS images relating to the signal to noise ratio (SNR). To counteract PVE, this paper proposes a novel Pairwise Mixture Model (PMM), that extends a recently reported Signal Mixture Model (SMM) for representing the MV-MRS signal as normal, low or high grade tissue types. Inspired by Conditional Random Field (CRF) and its continuous variant the PMM incorporates the surrounding voxel neighbourhood into an optimisation problem, the solution of which provides an estimation to a set of coefficients. The values of the estimated coefficients represents the amount of each tissue type (normal, low or high) found within a voxel. These coefficients can then be visualised as a nosological rendering using a coloured grid representing the MV-MRS image overlaid on top of a structural image, such as a Magnetic Resonance Image (MRI). Experimental results show an accuracy of 92.69% in classifying patient tumours as either low or high grade compared against the histopathology for each patient. Compared to 91.96% achieved by the SMM, the proposed PMM method demonstrates the importance of incorporating spatial coherence into the estimation as well as its potential clinical usage.

A nonlinear isobologram model with Box-Cox transformation to both sides for chemical mixtures.

PubMed

Chen, D G; Pounds, J G

1998-12-01

The linear logistical isobologram is a commonly used and powerful graphical and statistical tool for analyzing the combined effects of simple chemical mixtures. In this paper a nonlinear isobologram model is proposed to analyze the joint action of chemical mixtures for quantitative dose-response relationships. This nonlinear isobologram model incorporates two additional new parameters, Ymin and Ymax, to facilitate analysis of response data that are not constrained between 0 and 1, where parameters Ymin and Ymax represent the minimal and the maximal observed toxic response. This nonlinear isobologram model for binary mixtures can be expressed as [formula: see text] In addition, a Box-Cox transformation to both sides is introduced to improve the goodness of fit and to provide a more robust model for achieving homogeneity and normality of the residuals. Finally, a confidence band is proposed for selected isobols, e.g., the median effective dose, to facilitate graphical and statistical analysis of the isobologram. The versatility of this approach is demonstrated using published data describing the toxicity of the binary mixtures of citrinin and ochratoxin as well as a new experimental data from our laboratory for mixtures of mercury and cadmium.

A nonlinear isobologram model with Box-Cox transformation to both sides for chemical mixtures.

PubMed Central

Chen, D G; Pounds, J G

1998-01-01

The linear logistical isobologram is a commonly used and powerful graphical and statistical tool for analyzing the combined effects of simple chemical mixtures. In this paper a nonlinear isobologram model is proposed to analyze the joint action of chemical mixtures for quantitative dose-response relationships. This nonlinear isobologram model incorporates two additional new parameters, Ymin and Ymax, to facilitate analysis of response data that are not constrained between 0 and 1, where parameters Ymin and Ymax represent the minimal and the maximal observed toxic response. This nonlinear isobologram model for binary mixtures can be expressed as [formula: see text] In addition, a Box-Cox transformation to both sides is introduced to improve the goodness of fit and to provide a more robust model for achieving homogeneity and normality of the residuals. Finally, a confidence band is proposed for selected isobols, e.g., the median effective dose, to facilitate graphical and statistical analysis of the isobologram. The versatility of this approach is demonstrated using published data describing the toxicity of the binary mixtures of citrinin and ochratoxin as well as a new experimental data from our laboratory for mixtures of mercury and cadmium. PMID:9860894

Factorial Design Approach in Proportioning Prestressed Self-Compacting Concrete

PubMed Central

Long, Wu-Jian; Khayat, Kamal Henri; Lemieux, Guillaume; Xing, Feng; Wang, Wei-Lun

2015-01-01

In order to model the effect of mixture parameters and material properties on the hardened properties of, prestressed self-compacting concrete (SCC), and also to investigate the extensions of the statistical models, a factorial design was employed to identify the relative significance of these primary parameters and their interactions in terms of the mechanical and visco-elastic properties of SCC. In addition to the 16 fractional factorial mixtures evaluated in the modeled region of −1 to +1, eight axial mixtures were prepared at extreme values of −2 and +2 with the other variables maintained at the central points. Four replicate central mixtures were also evaluated. The effects of five mixture parameters, including binder type, binder content, dosage of viscosity-modifying admixture (VMA), water-cementitious material ratio (w/cm), and sand-to-total aggregate ratio (S/A) on compressive strength, modulus of elasticity, as well as autogenous and drying shrinkage are discussed. The applications of the models to better understand trade-offs between mixture parameters and carry out comparisons among various responses are also highlighted. A logical design approach would be to use the existing model to predict the optimal design, and then run selected tests to quantify the influence of the new binder on the model. PMID:28787990

NGMIX: Gaussian mixture models for 2D images

NASA Astrophysics Data System (ADS)

Sheldon, Erin

2015-08-01

NGMIX implements Gaussian mixture models for 2D images. Both the PSF profile and the galaxy are modeled using mixtures of Gaussians. Convolutions are thus performed analytically, resulting in fast model generation as compared to methods that perform the convolution in Fourier space. For the galaxy model, NGMIX supports exponential disks and de Vaucouleurs and Sérsic profiles; these are implemented approximately as a sum of Gaussians using the fits from Hogg & Lang (2013). Additionally, any number of Gaussians can be fit, either completely free or constrained to be cocentric and co-elliptical.

A non-ideal model for predicting the effect of dissolved salt on the flash point of solvent mixtures.

PubMed

Liaw, Horng-Jang; Wang, Tzu-Ai

2007-03-06

Flash point is one of the major quantities used to characterize the fire and explosion hazard of liquids. Herein, a liquid with dissolved salt is presented in a salt-distillation process for separating close-boiling or azeotropic systems. The addition of salts to a liquid may reduce fire and explosion hazard. In this study, we have modified a previously proposed model for predicting the flash point of miscible mixtures to extend its application to solvent/salt mixtures. This modified model was verified by comparison with the experimental data for organic solvent/salt and aqueous-organic solvent/salt mixtures to confirm its efficacy in terms of prediction of the flash points of these mixtures. The experimental results confirm marked increases in liquid flash point increment with addition of inorganic salts relative to supplementation with equivalent quantities of water. Based on this evidence, it appears reasonable to suggest potential application for the model in assessment of the fire and explosion hazard for solvent/salt mixtures and, further, that addition of inorganic salts may prove useful for hazard reduction in flammable liquids.

Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teng, S.; Tebby, C.

Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro – in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-timemore » cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. - Highlights: • We could predict cell response over repeated exposure to mixtures of cosmetics. • Compounds acted independently on the cells. • Metabolic interactions impacted exposure concentrations to the compounds.« less

Determination of Failure Point of Asphalt-Mixture Fatigue-Test Results Using the Flow Number Method

NASA Astrophysics Data System (ADS)

Wulan, C. E. P.; Setyawan, A.; Pramesti, F. P.

2018-03-01

The failure point of the results of fatigue tests of asphalt mixtures performed in controlled stress mode is difficult to determine. However, several methods from empirical studies are available to solve this problem. The objectives of this study are to determine the fatigue failure point of the results of indirect tensile fatigue tests using the Flow Number Method and to determine the best Flow Number model for the asphalt mixtures tested. In order to achieve these goals, firstly the best asphalt mixture of three was selected based on their Marshall properties. Next, the Indirect Tensile Fatigue Test was performed on the chosen asphalt mixture. The stress-controlled fatigue tests were conducted at a temperature of 20°C and frequency of 10 Hz, with the application of three loads: 500, 600, and 700 kPa. The last step was the application of the Flow Number methods, namely the Three-Stages Model, FNest Model, Francken Model, and Stepwise Method, to the results of the fatigue tests to determine the failure point of the specimen. The chosen asphalt mixture is EVA (Ethyl Vinyl Acetate) polymer -modified asphalt mixture with 6.5% OBC (Optimum Bitumen Content). Furthermore, the result of this study shows that the failure points of the EVA-modified asphalt mixture under loads of 500, 600, and 700 kPa are 6621, 4841, and 611 for the Three-Stages Model; 4271, 3266, and 537 for the FNest Model; 3401, 2431, and 421 for the Francken Model, and 6901, 6841, and 1291 for the Stepwise Method, respectively. These different results show that the bigger the loading, the smaller the number of cycles to failure. However, the best FN results are shown by the Three-Stages Model and the Stepwise Method, which exhibit extreme increases after the constant development of accumulated strain.

Continuous movement decoding using a target-dependent model with EMG inputs.

PubMed

Sachs, Nicholas A; Corbett, Elaine A; Miller, Lee E; Perreault, Eric J

2011-01-01

Trajectory-based models that incorporate target position information have been shown to accurately decode reaching movements from bio-control signals, such as muscle (EMG) and cortical activity (neural spikes). One major hurdle in implementing such models for neuroprosthetic control is that they are inherently designed to decode single reaches from a position of origin to a specific target. Gaze direction can be used to identify appropriate targets, however information regarding movement intent is needed to determine when a reach is meant to begin and when it has been completed. We used linear discriminant analysis to classify limb states into movement classes based on recorded EMG from a sparse set of shoulder muscles. We then used the detected state transitions to update target information in a mixture of Kalman filters that incorporated target position explicitly in the state, and used EMG activity to decode arm movements. Updating the target position initiated movement along new trajectories, allowing a sequence of appropriately timed single reaches to be decoded in series and enabling highly accurate continuous control.

Model Selection Methods for Mixture Dichotomous IRT Models

ERIC Educational Resources Information Center

Li, Feiming; Cohen, Allan S.; Kim, Seock-Ho; Cho, Sun-Joo

2009-01-01

This study examines model selection indices for use with dichotomous mixture item response theory (IRT) models. Five indices are considered: Akaike's information coefficient (AIC), Bayesian information coefficient (BIC), deviance information coefficient (DIC), pseudo-Bayes factor (PsBF), and posterior predictive model checks (PPMC). The five…

Size-distribution analysis of macromolecules by sedimentation velocity ultracentrifugation and lamm equation modeling.

PubMed

Schuck, P

2000-03-01

A new method for the size-distribution analysis of polymers by sedimentation velocity analytical ultracentrifugation is described. It exploits the ability of Lamm equation modeling to discriminate between the spreading of the sedimentation boundary arising from sample heterogeneity and from diffusion. Finite element solutions of the Lamm equation for a large number of discrete noninteracting species are combined with maximum entropy regularization to represent a continuous size-distribution. As in the program CONTIN, the parameter governing the regularization constraint is adjusted by variance analysis to a predefined confidence level. Estimates of the partial specific volume and the frictional ratio of the macromolecules are used to calculate the diffusion coefficients, resulting in relatively high-resolution sedimentation coefficient distributions c(s) or molar mass distributions c(M). It can be applied to interference optical data that exhibit systematic noise components, and it does not require solution or solvent plateaus to be established. More details on the size-distribution can be obtained than from van Holde-Weischet analysis. The sensitivity to the values of the regularization parameter and to the shape parameters is explored with the help of simulated sedimentation data of discrete and continuous model size distributions, and by applications to experimental data of continuous and discrete protein mixtures.

Change of hydrogen bonding structure in ionic liquid mixtures by anion type

NASA Astrophysics Data System (ADS)

Cha, Seoncheol; Kim, Doseok

2018-05-01

Ionic liquid mixtures have gained attention as a way of tuning material properties continuously with composition changes. For some mixture systems, physicochemical properties such as excess molar volume have been found to be significantly different from the value expected by linear interpolation, but the origin of this deviation is not well understood yet. The microstructure of the mixture, which can range from an ideal mixture of two initial consisting ionic liquids to a different structure from those of pure materials, has been suggested as the origin of the observed deviation. The structures of several different ionic liquid mixtures are studied by IR spectroscopy to confirm this suggestion, as a particular IR absorption band (νC(2)-D) for the moiety participating in the hydrogen bonding changes sensitively with the change of the anion in the ionic liquid. The absorbance of νC(2)-D changes proportionally with the composition, and a relatively small excess molar volume is observed for the mixtures containing an electronegative halide anion. By contrast, the absorbance changes nonlinearly, and the excess molar volumes are larger for the mixtures of which one of the anions has multiple interaction sites.

Mixture models for estimating the size of a closed population when capture rates vary among individuals

USGS Publications Warehouse

Dorazio, R.M.; Royle, J. Andrew

2003-01-01

We develop a parameterization of the beta-binomial mixture that provides sensible inferences about the size of a closed population when probabilities of capture or detection vary among individuals. Three classes of mixture models (beta-binomial, logistic-normal, and latent-class) are fitted to recaptures of snowshoe hares for estimating abundance and to counts of bird species for estimating species richness. In both sets of data, rates of detection appear to vary more among individuals (animals or species) than among sampling occasions or locations. The estimates of population size and species richness are sensitive to model-specific assumptions about the latent distribution of individual rates of detection. We demonstrate using simulation experiments that conventional diagnostics for assessing model adequacy, such as deviance, cannot be relied on for selecting classes of mixture models that produce valid inferences about population size. Prior knowledge about sources of individual heterogeneity in detection rates, if available, should be used to help select among classes of mixture models that are to be used for inference.

Chemical mixtures in potable water in the U.S.

USGS Publications Warehouse

Ryker, Sarah J.

2014-01-01

In recent years, regulators have devoted increasing attention to health risks from exposure to multiple chemicals. In 1996, the US Congress directed the US Environmental Protection Agency (EPA) to study mixtures of chemicals in drinking water, with a particular focus on potential interactions affecting chemicals' joint toxicity. The task is complicated by the number of possible mixtures in drinking water and lack of toxicological data for combinations of chemicals. As one step toward risk assessment and regulation of mixtures, the EPA and the Agency for Toxic Substances and Disease Registry (ATSDR) have proposed to estimate mixtures' toxicity based on the interactions of individual component chemicals. This approach permits the use of existing toxicological data on individual chemicals, but still requires additional information on interactions between chemicals and environmental data on the public's exposure to combinations of chemicals. Large compilations of water-quality data have recently become available from federal and state agencies. This chapter demonstrates the use of these environmental data, in combination with the available toxicological data, to explore scenarios for mixture toxicity and develop priorities for future research and regulation. Occurrence data on binary and ternary mixtures of arsenic, cadmium, and manganese are used to parameterize the EPA and ATSDR models for each drinking water source in the dataset. The models' outputs are then mapped at county scale to illustrate the implications of the proposed models for risk assessment and rulemaking. For example, according to the EPA's interaction model, the levels of arsenic and cadmium found in US groundwater are unlikely to have synergistic cardiovascular effects in most areas of the country, but the same mixture's potential for synergistic neurological effects merits further study. Similar analysis could, in future, be used to explore the implications of alternative risk models for the toxicity and interaction of complex mixtures, and to identify the communities with the highest and lowest expected value for regulation of chemical mixtures.

The Cramér-Rao Bounds and Sensor Selection for Nonlinear Systems with Uncertain Observations.

PubMed

Wang, Zhiguo; Shen, Xiaojing; Wang, Ping; Zhu, Yunmin

2018-04-05

This paper considers the problems of the posterior Cramér-Rao bound and sensor selection for multi-sensor nonlinear systems with uncertain observations. In order to effectively overcome the difficulties caused by uncertainty, we investigate two methods to derive the posterior Cramér-Rao bound. The first method is based on the recursive formula of the Cramér-Rao bound and the Gaussian mixture model. Nevertheless, it needs to compute a complex integral based on the joint probability density function of the sensor measurements and the target state. The computation burden of this method is relatively high, especially in large sensor networks. Inspired by the idea of the expectation maximization algorithm, the second method is to introduce some 0-1 latent variables to deal with the Gaussian mixture model. Since the regular condition of the posterior Cramér-Rao bound is unsatisfied for the discrete uncertain system, we use some continuous variables to approximate the discrete latent variables. Then, a new Cramér-Rao bound can be achieved by a limiting process of the Cramér-Rao bound of the continuous system. It avoids the complex integral, which can reduce the computation burden. Based on the new posterior Cramér-Rao bound, the optimal solution of the sensor selection problem can be derived analytically. Thus, it can be used to deal with the sensor selection of a large-scale sensor networks. Two typical numerical examples verify the effectiveness of the proposed methods.

Review of stochastic hybrid systems with applications in biological systems modeling and analysis.

PubMed

Li, Xiangfang; Omotere, Oluwaseyi; Qian, Lijun; Dougherty, Edward R

2017-12-01

Stochastic hybrid systems (SHS) have attracted a lot of research interests in recent years. In this paper, we review some of the recent applications of SHS to biological systems modeling and analysis. Due to the nature of molecular interactions, many biological processes can be conveniently described as a mixture of continuous and discrete phenomena employing SHS models. With the advancement of SHS theory, it is expected that insights can be obtained about biological processes such as drug effects on gene regulation. Furthermore, combining with advanced experimental methods, in silico simulations using SHS modeling techniques can be carried out for massive and rapid verification or falsification of biological hypotheses. The hope is to substitute costly and time-consuming in vitro or in vivo experiments or provide guidance for those experiments and generate better hypotheses.

A path integral methodology for obtaining thermodynamic properties of nonadiabatic systems using Gaussian mixture distributions

NASA Astrophysics Data System (ADS)

Raymond, Neil; Iouchtchenko, Dmitri; Roy, Pierre-Nicholas; Nooijen, Marcel

2018-05-01

We introduce a new path integral Monte Carlo method for investigating nonadiabatic systems in thermal equilibrium and demonstrate an approach to reducing stochastic error. We derive a general path integral expression for the partition function in a product basis of continuous nuclear and discrete electronic degrees of freedom without the use of any mapping schemes. We separate our Hamiltonian into a harmonic portion and a coupling portion; the partition function can then be calculated as the product of a Monte Carlo estimator (of the coupling contribution to the partition function) and a normalization factor (that is evaluated analytically). A Gaussian mixture model is used to evaluate the Monte Carlo estimator in a computationally efficient manner. Using two model systems, we demonstrate our approach to reduce the stochastic error associated with the Monte Carlo estimator. We show that the selection of the harmonic oscillators comprising the sampling distribution directly affects the efficiency of the method. Our results demonstrate that our path integral Monte Carlo method's deviation from exact Trotter calculations is dominated by the choice of the sampling distribution. By improving the sampling distribution, we can drastically reduce the stochastic error leading to lower computational cost.

Structure and Energetics of Clusters Relevant to Thorium Tetrachloride Melts

NASA Astrophysics Data System (ADS)

Akdeniz, Z.; Tosi, M. P.

2000-10-01

We study within an ionic model the structure and energetics of neutral and charged molecular clusters which may be relevant to molten ThCl4 and to its liquid mixtures with alkali chlorides, with reference to Raman scattering experiments by Photiadis and Papatheodorou. As stressed by these authors, the most striking facts for ThCl4 in comparison to other tetrachloride compounds (and in particular to ZrCl4) are the appreciable ionic conductivity of the pure melt and the continuous structural changes which occur in the melt mixtures with varying composition. After adjusting our model to data on the isolated ThCl4 tetrahedral molecule, we evaluate (i) the Th2Cl8 dimer and the singly charged species obtained from it by chlorine-ion transfer between two such neutral dimers; (ii) the ThCl6 and ThCl7 clusters both as charged anions and as alkali-compensated species; and (iii) various oligomers carrying positive or negative double charges. Our study shows that the characteristic structural properties of the ThCl4 compound and of the alkali-Th chloride systems are the consequence of the relatively high ionic character of the binding, which is already evident in the isolated ThCl4 monomer.

Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs.

PubMed

Saunders, Christopher T; Wong, Wendy S W; Swamy, Sajani; Becq, Jennifer; Murray, Lisa J; Cheetham, R Keira

2012-07-15

Whole genome and exome sequencing of matched tumor-normal sample pairs is becoming routine in cancer research. The consequent increased demand for somatic variant analysis of paired samples requires methods specialized to model this problem so as to sensitively call variants at any practical level of tumor impurity. We describe Strelka, a method for somatic SNV and small indel detection from sequencing data of matched tumor-normal samples. The method uses a novel Bayesian approach which represents continuous allele frequencies for both tumor and normal samples, while leveraging the expected genotype structure of the normal. This is achieved by representing the normal sample as a mixture of germline variation with noise, and representing the tumor sample as a mixture of the normal sample with somatic variation. A natural consequence of the model structure is that sensitivity can be maintained at high tumor impurity without requiring purity estimates. We demonstrate that the method has superior accuracy and sensitivity on impure samples compared with approaches based on either diploid genotype likelihoods or general allele-frequency tests. The Strelka workflow source code is available at ftp://strelka@ftp.illumina.com/. csaunders@illumina.com

Parametric identification of the process of preparing ceramic mixture as an object of control

NASA Astrophysics Data System (ADS)

Galitskov, Stanislav; Nazarov, Maxim; Galitskov, Konstantin

2017-10-01

Manufacture of ceramic materials and products largely depends on the preparation of clay raw materials. The main process here is the process of mixing, which in industrial production is mostly done in cross-compound clay mixers of continuous operation with steam humidification. The authors identified features of dynamics of this technological stage, which in itself is a non-linear control object with distributed parameters. When solving practical tasks for automation of a certain class of ceramic materials production it is important to make parametric identification of moving clay. In this paper the task is solved with the use of computational models, approximated to a particular section of a clay mixer along its length. The research introduces a methodology of computational experiments as applied to the designed computational model. Parametric identification of dynamic links was carried out according to transient characteristics. The experiments showed that the control object in question is to a great extent a non-stationary one. The obtained results are problematically oriented on synthesizing a multidimensional automatic control system for preparation of ceramic mixture with specified values of humidity and temperature exposed to the technological process of major disturbances.

Testing and Improving Theories of Radiative Transfer for Determining the Mineralogy of Planetary Surfaces

NASA Astrophysics Data System (ADS)

Gudmundsson, E.; Ehlmann, B. L.; Mustard, J. F.; Hiroi, T.; Poulet, F.

2012-12-01

Two radiative transfer theories, the Hapke and Shkuratov models, have been used to estimate the mineralogic composition of laboratory mixtures of anhydrous mafic minerals from reflected near-infrared light, accurately modeling abundances to within 10%. For this project, we tested the efficacy of the Hapke model for determining the composition of mixtures (weight fraction, particle diameter) containing hydrous minerals, including phyllosilicates. Modal mineral abundances for some binary mixtures were modeled to +/-10% of actual values, but other mixtures showed higher inaccuracies (up to 25%). Consequently, a sensitivity analysis of selected input and model parameters was performed. We first examined the shape of the model's error function (RMS error between modeled and measured spectra) over a large range of endmember weight fractions and particle diameters and found that there was a single global minimum for each mixture (rather than local minima). The minimum was sensitive to modeled particle diameter but comparatively insensitive to modeled endmember weight fraction. Derivation of the endmembers' k optical constant spectra using the Hapke model showed differences with the Shkuratov-derived optical constants originally used. Model runs with different sets of optical constants suggest that slight differences in the optical constants used significantly affect the accuracy of model predictions. Even for mixtures where abundance was modeled correctly, particle diameter agreed inconsistently with sieved particle sizes and varied greatly for individual mix within suite. Particle diameter was highly sensitive to the optical constants, possibly indicating that changes in modeled path length (proportional to particle diameter) compensate for changes in the k optical constant. Alternatively, it may not be appropriate to model path length and particle diameter with the same proportionality for all materials. Across mixtures, RMS error increased in proportion to the fraction of the darker endmember. Analyses are ongoing and further studies will investigate the effect of sample hydration, permitted variability in particle size, assumed photometric functions and use of different wavelength ranges on model results. Such studies will advance understanding of how to best apply radiative transfer modeling to geologically complex planetary surfaces. Corresponding authors: eyjolfur88@gmail.com, ehlmann@caltech.edu

Applying mixture toxicity modelling to predict bacterial bioluminescence inhibition by non-specifically acting pharmaceuticals and specifically acting antibiotics.

PubMed

Neale, Peta A; Leusch, Frederic D L; Escher, Beate I

2017-04-01

Pharmaceuticals and antibiotics co-occur in the aquatic environment but mixture studies to date have mainly focused on pharmaceuticals alone or antibiotics alone, although differences in mode of action may lead to different effects in mixtures. In this study we used the Bacterial Luminescence Toxicity Screen (BLT-Screen) after acute (0.5 h) and chronic (16 h) exposure to evaluate how non-specifically acting pharmaceuticals and specifically acting antibiotics act together in mixtures. Three models were applied to predict mixture toxicity including concentration addition, independent action and the two-step prediction (TSP) model, which groups similarly acting chemicals together using concentration addition, followed by independent action to combine the two groups. All non-antibiotic pharmaceuticals had similar EC 50 values at both 0.5 and 16 h, indicating together with a QSAR (Quantitative Structure-Activity Relationship) analysis that they act as baseline toxicants. In contrast, the antibiotics' EC 50 values decreased by up to three orders of magnitude after 16 h, which can be explained by their specific effect on bacteria. Equipotent mixtures of non-antibiotic pharmaceuticals only, antibiotics only and both non-antibiotic pharmaceuticals and antibiotics were prepared based on the single chemical results. The mixture toxicity models were all in close agreement with the experimental results, with predicted EC 50 values within a factor of two of the experimental results. This suggests that concentration addition can be applied to bacterial assays to model the mixture effects of environmental samples containing both specifically and non-specifically acting chemicals. Copyright © 2017 Elsevier Ltd. All rights reserved.

Single-bubble sonoluminescence in sulfuric acid and water: bubble dynamics, stability, and continuous spectra.

PubMed

Puente, Gabriela F; García-Martínez, Pablo; Bonetto, Fabián J

2007-01-01

We present theoretical calculations of an argon bubble in a liquid solution of 85%wt sulfuric acid and 15%wt water in single-bubble sonoluminescence. We used a model without free parameters to be adjusted. We predict from first principles the region in parameter space for stable bubble evolution, the temporal evolution of the bubble radius, the maximum temperature, pressures, and the light spectra due to thermal emissions. We also used a partial differential equation based model (hydrocode) to compute the temperature and pressure evolutions at the center of the bubble during maximum compression. We found the behavior of this liquid mixture to be very different from water in several aspects. Most of the models in sonoluminescence were compared with water experimental results.

Bunte Breccia of the Ries - Continuous deposits of large impact craters

NASA Technical Reports Server (NTRS)

Horz, F.; Ostertag, R.; Rainey, D. A.

1983-01-01

The 26-km-diameter Ries impact crater in south Germany and the mechanism of ejection and emplacement associated with its formation about 15 Myr ago are discussed in detail, and the implications of the findings for models of crater formation on earth, moon, and planets are considered. Field observations and laboratory tests on 560-m core materials from nine locations are reported. The continuous deposits (Bunte Breccia) are found to be a chaotic mixture resulting from deposition at ambient temperatures in a highly turbulent environment, probably in the ballistic scenario proposed by Oberbeck et al. (1975), with an emplacement time of only about 5 min. Further impact parameters are estimated using the 'Z model' of Maxwell (1977): initial radius = 6.5 km, excavation depth = 1650 m, excavation volume = 136 cu km, and transient cavity volume = 230 cu km. The interpretation of lunar and planetary remote-sensing and in situ evidence from impact craters is reviewed in the light of the Ries findings. Numerous photographs, maps, diagrams, and tables illustrate the investigation.

Ethanol fermentation integrated with PDMS composite membrane: An effective process.

PubMed

Fu, Chaohui; Cai, Di; Hu, Song; Miao, Qi; Wang, Yong; Qin, Peiyong; Wang, Zheng; Tan, Tianwei

2016-01-01

The polydimethylsiloxane (PDMS) membrane, prepared in water phase, was investigated in separation ethanol from model ethanol/water mixture and fermentation-pervaporation integrated process. Results showed that the PDMS membrane could effectively separate ethanol from model solution. When integrated with batch ethanol fermentation, the ethanol productivity was enhanced compared with conventional process. Fed-batch and continuous ethanol fermentation with pervaporation were also performed and studied. 396.2-663.7g/m(2)h and 332.4-548.1g/m(2)h of total flux with separation factor of 8.6-11.7 and 8-11.6, were generated in the fed-batch and continuous fermentation with pervaporation scenario, respectively. At the same time, high titre ethanol production of ∼417.2g/L and ∼446.3g/L were also achieved on the permeate side of membrane in the two scenarios, respectively. The integrated process was environmental friendly and energy saving, and has a promising perspective in long-terms operation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modelling the anaerobic digestion of solid organic waste - Substrate characterisation method for ADM1 using a combined biochemical and kinetic parameter estimation approach.

PubMed

Poggio, D; Walker, M; Nimmo, W; Ma, L; Pourkashanian, M

2016-07-01

This work proposes a novel and rigorous substrate characterisation methodology to be used with ADM1 to simulate the anaerobic digestion of solid organic waste. The proposed method uses data from both direct substrate analysis and the methane production from laboratory scale anaerobic digestion experiments and involves assessment of four substrate fractionation models. The models partition the organic matter into a mixture of particulate and soluble fractions with the decision on the most suitable model being made on quality of fit between experimental and simulated data and the uncertainty of the calibrated parameters. The method was tested using samples of domestic green and food waste and using experimental data from both short batch tests and longer semi-continuous trials. The results showed that in general an increased fractionation model complexity led to better fit but with increased uncertainty. When using batch test data the most suitable model for green waste included one particulate and one soluble fraction, whereas for food waste two particulate fractions were needed. With richer semi-continuous datasets, the parameter estimation resulted in less uncertainty therefore allowing the description of the substrate with a more complex model. The resulting substrate characterisations and fractionation models obtained from batch test data, for both waste samples, were used to validate the method using semi-continuous experimental data and showed good prediction of methane production, biogas composition, total and volatile solids, ammonia and alkalinity. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grove, John W.

We investigate sufficient conditions for thermodynamic consistency for equilibrium mixtures. Such models assume that the mass fraction average of the material component equations of state, when closed by a suitable equilibrium condition, provide a composite equation of state for the mixture. Here, we show that the two common equilibrium models of component pressure/temperature equilibrium and volume/temperature equilibrium (Dalton, 1808) define thermodynamically consistent mixture equations of state and that other equilibrium conditions can be thermodynamically consistent provided appropriate values are used for the mixture specific entropy and pressure.

Application of wavelet and Fuorier transforms as powerful alternatives for derivative spectrophotometry in analysis of binary mixtures: A comparative study

NASA Astrophysics Data System (ADS)

Hassan, Said A.; Abdel-Gawad, Sherif A.

2018-02-01

Two signal processing methods, namely, Continuous Wavelet Transform (CWT) and the second was Discrete Fourier Transform (DFT) were introduced as alternatives to the classical Derivative Spectrophotometry (DS) in analysis of binary mixtures. To show the advantages of these methods, a comparative study was performed on a binary mixture of Naltrexone (NTX) and Bupropion (BUP). The methods were compared by analyzing laboratory prepared mixtures of the two drugs. By comparing performance of the three methods, it was proved that CWT and DFT methods are more efficient and advantageous in analysis of mixtures with overlapped spectra than DS. The three signal processing methods were adopted for the quantification of NTX and BUP in pure and tablet forms. The adopted methods were validated according to the ICH guideline where accuracy, precision and specificity were found to be within appropriate limits.

Reducing Dangerous Effects of Unsymmetrical Dimethyl Hydrazine as a Liquid Propellant by Addition of Hydroxyethylhydrazine, Part II, Performance with Several Oxidizers

NASA Astrophysics Data System (ADS)

Keshavarz, Mohammad Hossein; Ramadan, Alireza; Mousaviazar, Ali; Zali, Abbas; Shokrollahi, Arash

2011-07-01

This work continues the study of suitable binary liquid mixtures of unsymmetrical dimethylhydrazine (UDMH) and hydroxyethylhydrazine (HEH) to reduce the harmful effects of pure UDMH. The synthesized HEH was mixed with UDMH up to 40 wt% of HEH to study the performance and properties of binary liquid mixtures of UDMH/HEH. The existence of strong hydrogen bonding between HEH and UDMH provides low-volatile mixtures of these hydrazine derivatives. The addition of HEH significantly reduces the vapor pressure of UDMH, thus reducing the known UDMH health risk to inhalation exposure. Specific impulse was used to study performance of binary mixture UDMH/HEH with respect to pure UDMH. A binary mixture of UDMH/HEH reacts spontaneously in contact with nitrogen tetroxide, red fuming nitric acid (RFNA), and inhibited red fuming nitric acid (IRFNA).

Polymeric compositions and their method of manufacture. [forming filled polymer systems using cryogenics

NASA Technical Reports Server (NTRS)

Moser, B. G.; Landel, R. F. (Inventor)

1972-01-01

Filled polymer compositions are made by dissolving the polymer binder in a suitable sublimable solvent, mixing the filler material with the polymer and its solvent, freezing the resultant mixture, and subliming the frozen solvent from the mixture from which it is then removed. The remaining composition is suitable for conventional processing such as compression molding or extruding. A particular feature of the method of manufacture is pouring the mixed solution slowly in a continuous stream into a cryogenic bath wherein frozen particles of the mixture result. The frozen individual particles are then subjected to the sublimation.

One-step catalytic conversion of biomass-derived carbohydrates to liquid fuels

DOEpatents

Sen, Ayusman; Yang, Weiran

2014-03-18

The invention relates to a method for manufacture of hydrocarbon fuels and oxygenated hydrocarbon fuels such as alkyl substituted tetrahydrofurans such as 2,5-dimethyltetrahydrofuran, 2-methyltetrahydrofuran, 5-methylfurfural and mixtures thereof. The method generally entails forming a mixture of reactants that includes carbonaceous material, water, a metal catalyst and an acid reacting that mixture in the presence of hydrogen. The reaction is performed at a temperature and for a time sufficient to produce a furan type hydrocarbon fuel. The process may be adapted to provide continuous manufacture of hydrocarbon fuels such as a furan type fuel.

Estimating and modeling the cure fraction in population-based cancer survival analysis.

PubMed

Lambert, Paul C; Thompson, John R; Weston, Claire L; Dickman, Paul W

2007-07-01

In population-based cancer studies, cure is said to occur when the mortality (hazard) rate in the diseased group of individuals returns to the same level as that expected in the general population. The cure fraction (the proportion of patients cured of disease) is of interest to patients and is a useful measure to monitor trends in survival of curable disease. There are 2 main types of cure fraction model, the mixture cure fraction model and the non-mixture cure fraction model, with most previous work concentrating on the mixture cure fraction model. In this paper, we extend the parametric non-mixture cure fraction model to incorporate background mortality, thus providing estimates of the cure fraction in population-based cancer studies. We compare the estimates of relative survival and the cure fraction between the 2 types of model and also investigate the importance of modeling the ancillary parameters in the selected parametric distribution for both types of model.

Process dissociation and mixture signal detection theory.

PubMed

DeCarlo, Lawrence T

2008-11-01

The process dissociation procedure was developed in an attempt to separate different processes involved in memory tasks. The procedure naturally lends itself to a formulation within a class of mixture signal detection models. The dual process model is shown to be a special case. The mixture signal detection model is applied to data from a widely analyzed study. The results suggest that a process other than recollection may be involved in the process dissociation procedure.

Evolution of mixed surfactant aggregates in solutions and at solid/solution interfaces

NASA Astrophysics Data System (ADS)

Zhang, Rui

Surfactant systems have been widely used in such as enhanced oil recovery, waste treatment and metallurgy, etc., in order to solve the problem of global energy crisis, to remove the pollutants and to generate novel energy resources. Almost all surfactant systems are invariably mixtures due to beneficial and economic considerations. The sizes and shapes of aggregates in solutions and at solid/solution interfaces become important, since the nanostructures of mixed aggregates determine solution and adsorption properties. A major hurdle in science is the lack of information on the type of complexes and aggregates formed by mixtures and the lack of techniques for deriving such information. Using techniques such as analytical ultracentrifuge, small angle neutron scattering, surface tension, fluorescence, cryo-TEM, light scattering and ultrafiltration, the nanostructures of aggregates of sugar based n-dodecyl-beta-D-maltoside (DM) and nonionic pentaethyleneglycol monododecyl ether or nonyl phenol ethoxylated decyl ether (NP-10) and their mixtures have been investigated to prove the hypothesis that the aggregation behavior is linked to packing of the surfactant governed by the molecular interactions as well as the molecular structures. The results from both sedimentation velocity and sedimentation equilibrium experiments suggest coexistence of two types of micelles in nonyl phenol ethoxylated decyl ether solutions and its mixtures with n-dodecyl-beta-D-maltoside while only one micellar species is present in n-dodecyl-beta-D-maltoside solutions, in good agreement with those from small angle neutron scattering, cryo-TEM, light scattering and ultrafiltration. Type I micelles were primary micelles at cmc while type II micelles were elongated micelles. On the other hand, the nanostructures of mixed surface aggregates have been quantitatively predicted for the first time using a modified packing index. As a continuation of the Somasundaran-Fuersteneau adsorption model, a modified one-step model has been developed to fully understand the adsorption behavior of surfactant mixtures and obtained thermodynamic information on aggregation number and standard free energy for surface aggregation. The findings are expected to provide fundamental basis for the design optimal surfactant schemes for desired purposes.

Statistical-thermodynamic model for light scattering from eye lens protein mixtures

NASA Astrophysics Data System (ADS)

Bell, Michael M.; Ross, David S.; Bautista, Maurino P.; Shahmohamad, Hossein; Langner, Andreas; Hamilton, John F.; Lahnovych, Carrie N.; Thurston, George M.

2017-02-01

We model light-scattering cross sections of concentrated aqueous mixtures of the bovine eye lens proteins γB- and α-crystallin by adapting a statistical-thermodynamic model of mixtures of spheres with short-range attractions. The model reproduces measured static light scattering cross sections, or Rayleigh ratios, of γB-α mixtures from dilute concentrations where light scattering intensity depends on molecular weights and virial coefficients, to realistically high concentration protein mixtures like those of the lens. The model relates γB-γB and γB-α attraction strengths and the γB-α size ratio to the free energy curvatures that set light scattering efficiency in tandem with protein refractive index increments. The model includes (i) hard-sphere α-α interactions, which create short-range order and transparency at high protein concentrations, (ii) short-range attractive plus hard-core γ-γ interactions, which produce intense light scattering and liquid-liquid phase separation in aqueous γ-crystallin solutions, and (iii) short-range attractive plus hard-core γ-α interactions, which strongly influence highly non-additive light scattering and phase separation in concentrated γ-α mixtures. The model reveals a new lens transparency mechanism, that prominent equilibrium composition fluctuations can be perpendicular to the refractive index gradient. The model reproduces the concave-up dependence of the Rayleigh ratio on α/γ composition at high concentrations, its concave-down nature at intermediate concentrations, non-monotonic dependence of light scattering on γ-α attraction strength, and more intricate, temperature-dependent features. We analytically compute the mixed virial series for light scattering efficiency through third order for the sticky-sphere mixture, and find that the full model represents the available light scattering data at concentrations several times those where the second and third mixed virial contributions fail. The model indicates that increased γ-γ attraction can raise γ-α mixture light scattering far more than it does for solutions of γ-crystallin alone, and can produce marked turbidity tens of degrees celsius above liquid-liquid separation.

Toxicity interactions between manganese (Mn) and lead (Pb) or cadmium (Cd) in a model organism the nematode C. elegans.

PubMed

Lu, Cailing; Svoboda, Kurt R; Lenz, Kade A; Pattison, Claire; Ma, Hongbo

2018-06-01

Manganese (Mn) is considered as an emerging metal contaminant in the environment. However, its potential interactions with companying toxic metals and the associated mixture effects are largely unknown. Here, we investigated the toxicity interactions between Mn and two commonly seen co-occurring toxic metals, Pb and Cd, in a model organism the nematode Caenorhabditis elegans. The acute lethal toxicity of mixtures of Mn+Pb and Mn+Cd were first assessed using a toxic unit model. Multiple toxicity endpoints including reproduction, lifespan, stress response, and neurotoxicity were then examined to evaluate the mixture effects at sublethal concentrations. Stress response was assessed using a daf-16::GFP transgenic strain that expresses GFP under the control of DAF-16 promotor. Neurotoxicity was assessed using a dat-1::GFP transgenic strain that expresses GFP in dopaminergic neurons. The mixture of Mn+Pb induced a more-than-additive (synergistic) lethal toxicity in the worm whereas the mixture of Mn+Cd induced a less-than-additive (antagonistic) toxicity. Mixture effects on sublethal toxicity showed more complex patterns and were dependent on the toxicity endpoints as well as the modes of toxic action of the metals. The mixture of Mn+Pb induced additive effects on both reproduction and lifespan, whereas the mixture of Mn+Cd induced additive effects on lifespan but not reproduction. Both mixtures seemed to induce additive effects on stress response and neurotoxicity, although a quantitative assessment was not possible due to the single concentrations used in mixture tests. Our findings demonstrate the complexity of metal interactions and the associated mixture effects. Assessment of metal mixture toxicity should take into consideration the unique property of individual metals, their potential toxicity mechanisms, and the toxicity endpoints examined.

Communication: Modeling electrolyte mixtures with concentration dependent dielectric permittivity

NASA Astrophysics Data System (ADS)

Chen, Hsieh; Panagiotopoulos, Athanassios Z.

2018-01-01

We report a new implicit-solvent simulation model for electrolyte mixtures based on the concept of concentration dependent dielectric permittivity. A combining rule is found to predict the dielectric permittivity of electrolyte mixtures based on the experimentally measured dielectric permittivity for pure electrolytes as well as the mole fractions of the electrolytes in mixtures. Using grand canonical Monte Carlo simulations, we demonstrate that this approach allows us to accurately reproduce the mean ionic activity coefficients of NaCl in NaCl-CaCl2 mixtures at ionic strengths up to I = 3M. These results are important for thermodynamic studies of geologically relevant brines and physiological fluids.

Variable selection in a flexible parametric mixture cure model with interval-censored data.

PubMed

Scolas, Sylvie; El Ghouch, Anouar; Legrand, Catherine; Oulhaj, Abderrahim

2016-03-30

In standard survival analysis, it is generally assumed that every individual will experience someday the event of interest. However, this is not always the case, as some individuals may not be susceptible to this event. Also, in medical studies, it is frequent that patients come to scheduled interviews and that the time to the event is only known to occur between two visits. That is, the data are interval-censored with a cure fraction. Variable selection in such a setting is of outstanding interest. Covariates impacting the survival are not necessarily the same as those impacting the probability to experience the event. The objective of this paper is to develop a parametric but flexible statistical model to analyze data that are interval-censored and include a fraction of cured individuals when the number of potential covariates may be large. We use the parametric mixture cure model with an accelerated failure time regression model for the survival, along with the extended generalized gamma for the error term. To overcome the issue of non-stable and non-continuous variable selection procedures, we extend the adaptive LASSO to our model. By means of simulation studies, we show good performance of our method and discuss the behavior of estimates with varying cure and censoring proportion. Lastly, our proposed method is illustrated with a real dataset studying the time until conversion to mild cognitive impairment, a possible precursor of Alzheimer's disease. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

40 CFR 265.198 - Special requirements for ignitable or reactive wastes.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) The resulting waste, mixture, or dissolved material no longer meets the definition of ignitable or... reactive wastes. 265.198 Section 265.198 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES (CONTINUED) INTERIM STATUS STANDARDS FOR OWNERS AND OPERATORS OF HAZARDOUS WASTE...

Mixture IRT Model with a Higher-Order Structure for Latent Traits

ERIC Educational Resources Information Center

Huang, Hung-Yu

2017-01-01

Mixture item response theory (IRT) models have been suggested as an efficient method of detecting the different response patterns derived from latent classes when developing a test. In testing situations, multiple latent traits measured by a battery of tests can exhibit a higher-order structure, and mixtures of latent classes may occur on…

Beta Regression Finite Mixture Models of Polarization and Priming

ERIC Educational Resources Information Center

Smithson, Michael; Merkle, Edgar C.; Verkuilen, Jay

2011-01-01

This paper describes the application of finite-mixture general linear models based on the beta distribution to modeling response styles, polarization, anchoring, and priming effects in probability judgments. These models, in turn, enhance our capacity for explicitly testing models and theories regarding the aforementioned phenomena. The mixture…

Plasmachemical synthesis and evaluation of the thermal conductivity of metal-oxide compounds "Molybdenum-uranium dioxide"

NASA Astrophysics Data System (ADS)

Kotelnikova, Alexandra A.; Karengin, Alexander G.; Mendoza, Orlando

2018-03-01

The article represents possibility to apply oxidative and reducing plasma for plasma-chemical synthesis of metal-oxide compounds «Mo‒UO2» from water-salt mixtures «molybdic acid‒uranyl nitrate» and «molybdic acid‒ uranyl acetate». The composition of water-salt mixture was calculated and the conditions ensuring plasma-chemical synthesis of «Mo‒UO2» compounds were determined. Calculations were carried out at atmospheric pressure over a wide range of temperatures (300-4000 K), with the use of various plasma coolants (air, hydrogen). The heat conductivity coefficients of metal-oxide compounds «Mo‒UO2» consisting of continuous component (molybdenum matrix) are calculated. Inclusions from ceramics in the form of uranium dioxide were ordered in the matrix. Particular attention is paid to methods for calculating the coefficients of thermal conductivity of these compounds with the use of different models. Calculated results were compared with the experimental data.

Highly porous activated carbon based adsorption cooling system employing difluoromethane and a mixture of pentafluoroethane and difluoromethane

NASA Astrophysics Data System (ADS)

Askalany, Ahmed A.; Saha, Bidyut B.

2017-01-01

This paper presents a simulation for a low-grade thermally powered two-beds adsorption cooling system employing HFC-32 and a mixture of HFC-32 and HFC-125 (HFC-410a) with activated carbon of type Maxsorb III. The present simulation model adopts experimentally measured adsorption isotherms, adsorption kinetics and isosteric heat of adsorption data. Effect of operating conditions (mass flow rate of hot water, driving heat source temperature and evaporator temperature) on the system performance has been studied in detail. The simulation results showed that the system could be powered by low-grade heat source temperature (below 85 °C). AC/HFC-32 and AC/HFC-410a adsorption cooling cycles achieved close specific cooling power and coefficient of performance values of 0.15 kW/kg and 0.3, respectively at a regeneration temperature of 90 °C along with evaporator temperature of 10 °C. The investigated semi continuous adsorption cooling system could produce a cooling power of 9 kW.

Effective Ion Mobility Peak Width as a New Isomeric Descriptor for the Untargeted Analysis of Complex Mixtures Using Ion Mobility-Mass Spectrometry

NASA Astrophysics Data System (ADS)

Farenc, Mathilde; Paupy, Benoit; Marceau, Sabrina; Riches, Eleanor; Afonso, Carlos; Giusti, Pierre

2017-07-01

Ion mobility coupled with mass spectrometry was proven to be an efficient way to characterize complex mixtures such as petroleum samples. However, the identification of isomeric species is difficult owing to the molecular complexity of petroleum and no availability of standard molecules. This paper proposes a new simple indicator to estimate the isomeric content of highly complex mixtures. This indicator is based on the full width at half maximum (FWHM) of the extracted ion mobility peak measured in millisecond or square angstrom that is corrected for instrumental factors such as ion diffusion. This value can be easily obtained without precisely identifying the number of isomeric species under the ion mobility peaks. Considering the Boduszynski model, the ion mobility profile for a particular elemental composition is expected to be a continuum of various isomeric species. The drift time-dependent fragmentation profile was studied and confirmed this hypothesis, a continuous evolution of the fragmentation profile showing that the larger alkyl chain species were detected at higher drift time values. This new indicator was proven to be a fast and efficient method to compare vacuum gas oils for which no difference was found using other analytical techniques.

Endocrine, immune, and behavioral effects of aldicarb (carbamate), atrazine (triazine) and nitrate (fertilizer) mixtures at groundwater concentrations.

PubMed

Porter, W P; Jaeger, J W; Carlson, I H

1999-01-01

This paper describes the results of 5 years of research on interactive effects of mixtures of aldicarb, atrazine, and nitrate on endocrine, immune, and nervous system function. The concentrations of chemicals used were the same order of magnitude as current maximum contaminant levels (MCLs) for all three compounds. Such levels occur in groundwater across the United States. Dosing was through voluntary consumption of drinking water. We used fractional and full factorial designs with center replicates to determine multifactor effects. We used chronic doses in experiments that varied in duration from 22 to 103 days. We tested for changes in thyroid hormone levels, ability to make antibodies to foreign proteins, and aggression in wild deer mice, Peromyscus maniculatus, and white outbred Swiss Webster mice, Mus musculus, ND4 strain. Endocrine, immune, and behavior changes occurred due to doses of mixtures, but rarely due to single compounds at the same concentrations. Immune assay data suggest the possibility of seasonal effects at low doses. We present a multiple-level model to help interpret the data in the context of human health and biological conservation concerns. We discuss six testing deficiencies of currently registered pesticides, and suggest areas of human health concerns if present trends in pesticide use continue.

Suppression of turbulent energy cascade due to phase separation in homogenous binary mixture fluid

NASA Astrophysics Data System (ADS)

Takagi, Youhei; Okamoto, Sachiya

2015-11-01

When a multi-component fluid mixture becomes themophysically unstable state by quenching from well-melting condition, phase separation due to spinodal decomposition occurs, and a self-organized structure is formed. During phase separation, free energy is consumed for the structure formation. In our previous report, the phase separation in homogenous turbulence was numerically simulated and the coarsening process of phase separation was discussed. In this study, we extended our numerical model to a high Schmidt number fluid corresponding to actual polymer solution. The governing equations were continuity, Navier-Stokes, and Chan-Hiliard equations as same as our previous report. The flow filed was an isotropic homogenous turbulence, and the dimensionless parameters in the Chan-Hilliard equation were estimated based on the thermophysical condition of binary mixture. From the numerical results, it was found that turbulent energy cascade was drastically suppressed in the inertial subrange by phase separation for the high Schmidt number flow. By using the identification of turbulent and phase separation structure, we discussed the relation between total energy balance and the structures formation processes. This study is financially supported by the Grand-in-Aid for Young Scientists (B) (No. T26820045) from the Ministry of Education, Cul-ture, Sports, Science and Technology of Japan.

Predicting mixture toxicity of seven phenolic compounds with similar and dissimilar action mechanisms to Vibrio qinghaiensis sp.nov.Q67.

PubMed

Huang, Wei Ying; Liu, Fei; Liu, Shu Shen; Ge, Hui Lin; Chen, Hong Han

2011-09-01

The predictions of mixture toxicity for chemicals are commonly based on two models: concentration addition (CA) and independent action (IA). Whether the CA and IA can predict mixture toxicity of phenolic compounds with similar and dissimilar action mechanisms was studied. The mixture toxicity was predicted on the basis of the concentration-response data of individual compounds. Test mixtures at different concentration ratios and concentration levels were designed using two methods. The results showed that the Weibull function fit well with the concentration-response data of all the components and their mixtures, with all relative coefficients (Rs) greater than 0.99 and root mean squared errors (RMSEs) less than 0.04. The predicted values from CA and IA models conformed to observed values of the mixtures. Therefore, it can be concluded that both CA and IA can predict reliable results for the mixture toxicity of the phenolic compounds with similar and dissimilar action mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

Dynamic frailty models based on compound birth-death processes.

PubMed

Putter, Hein; van Houwelingen, Hans C

2015-07-01

Frailty models are used in survival analysis to model unobserved heterogeneity. They accommodate such heterogeneity by the inclusion of a random term, the frailty, which is assumed to multiply the hazard of a subject (individual frailty) or the hazards of all subjects in a cluster (shared frailty). Typically, the frailty term is assumed to be constant over time. This is a restrictive assumption and extensions to allow for time-varying or dynamic frailties are of interest. In this paper, we extend the auto-correlated frailty models of Henderson and Shimakura and of Fiocco, Putter and van Houwelingen, developed for longitudinal count data and discrete survival data, to continuous survival data. We present a rigorous construction of the frailty processes in continuous time based on compound birth-death processes. When the frailty processes are used as mixtures in models for survival data, we derive the marginal hazards and survival functions and the marginal bivariate survival functions and cross-ratio function. We derive distributional properties of the processes, conditional on observed data, and show how to obtain the maximum likelihood estimators of the parameters of the model using a (stochastic) expectation-maximization algorithm. The methods are applied to a publicly available data set. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Mixture optimization for mixed gas Joule-Thomson cycle

NASA Astrophysics Data System (ADS)

Detlor, J.; Pfotenhauer, J.; Nellis, G.

2017-12-01

An appropriate gas mixture can provide lower temperatures and higher cooling power when used in a Joule-Thomson (JT) cycle than is possible with a pure fluid. However, selecting gas mixtures to meet specific cooling loads and cycle parameters is a challenging design problem. This study focuses on the development of a computational tool to optimize gas mixture compositions for specific operating parameters. This study expands on prior research by exploring higher heat rejection temperatures and lower pressure ratios. A mixture optimization model has been developed which determines an optimal three-component mixture based on the analysis of the maximum value of the minimum value of isothermal enthalpy change, ΔhT , that occurs over the temperature range. This allows optimal mixture compositions to be determined for a mixed gas JT system with load temperatures down to 110 K and supply temperatures above room temperature for pressure ratios as small as 3:1. The mixture optimization model has been paired with a separate evaluation of the percent of the heat exchanger that exists in a two-phase range in order to begin the process of selecting a mixture for experimental investigation.

Existence, uniqueness and positivity of solutions for BGK models for mixtures

NASA Astrophysics Data System (ADS)

Klingenberg, C.; Pirner, M.

2018-01-01

We consider kinetic models for a multi component gas mixture without chemical reactions. In the literature, one can find two types of BGK models in order to describe gas mixtures. One type has a sum of BGK type interaction terms in the relaxation operator, for example the model described by Klingenberg, Pirner and Puppo [20] which contains well-known models of physicists and engineers for example Hamel [16] and Gross and Krook [15] as special cases. The other type contains only one collision term on the right-hand side, for example the well-known model of Andries, Aoki and Perthame [1]. For each of these two models [20] and [1], we prove existence, uniqueness and positivity of solutions in the first part of the paper. In the second part, we use the first model [20] in order to determine an unknown function in the energy exchange of the macroscopic equations for gas mixtures described by Dellacherie [11].

Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models.

PubMed

Teng, S; Tebby, C; Barcellini-Couget, S; De Sousa, G; Brochot, C; Rahmani, R; Pery, A R R

2016-08-15

Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro - in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. Copyright © 2016 Elsevier Inc. All rights reserved.

Dissociations of the number and precision of visual short-term memory representations in change detection.

PubMed

Xie, Weizhen; Zhang, Weiwei

2017-11-01

The present study dissociated the number (i.e., quantity) and precision (i.e., quality) of visual short-term memory (STM) representations in change detection using receiver operating characteristic (ROC) and experimental manipulations. Across three experiments, participants performed both recognition and recall tests of visual STM using the change-detection task and the continuous color-wheel recall task, respectively. Experiment 1 demonstrated that the estimates of the number and precision of visual STM representations based on the ROC model of change-detection performance were robustly correlated with the corresponding estimates based on the mixture model of continuous-recall performance. Experiments 2 and 3 showed that the experimental manipulation of mnemonic precision using white-noise masking and the experimental manipulation of the number of encoded STM representations using consolidation masking produced selective effects on the corresponding measures of mnemonic precision and the number of encoded STM representations, respectively, in both change-detection and continuous-recall tasks. Altogether, using the individual-differences (Experiment 1) and experimental dissociation (Experiment 2 and 3) approaches, the present study demonstrated the some-or-none nature of visual STM representations across recall and recognition.

Hydrogen isotope separation utilizing bulk getters

DOEpatents

Knize, R.J.; Cecchi, J.L.

1991-08-20

Tritium and deuterium are separated from a gaseous mixture thereof, derived from a nuclear fusion reactor or some other source, by providing a casing with a bulk getter therein for absorbing the gaseous mixture to produce an initial loading of the getter, partially desorbing the getter to produce a desorbed mixture which is tritium-enriched, pumping the desorbed mixture into a separate container, the remaining gaseous loading in the getter being deuterium-enriched, desorbing the getter to a substantially greater extent to produce a deuterium-enriched gaseous mixture, and removing the deuterium-enriched mixture into another container. The bulk getter may comprise a zirconium-aluminum alloy, or a zirconium-vanadium-iron alloy. The partial desorption may reduce the loading by approximately fifty percent. The basic procedure may be extended to produce a multistage isotope separator, including at least one additional bulk getter into which the tritium-enriched mixture is absorbed. The second getter is then partially desorbed to produce a desorbed mixture which is further tritium-enriched. The last-mentioned mixture is then removed from the container for the second getter, which is then desorbed to a substantially greater extent to produce a desorbed mixture which is deuterium-enriched. The last-mentioned mixture is then removed so that the cycle can be continued and repeated. The method of isotope separation is also applicable to other hydrogen isotopes, in that the method can be employed for separating either deuterium or tritium from normal hydrogen. 4 figures.

Hydrogen isotope separation utilizing bulk getters

DOEpatents

Knize, Randall J.; Cecchi, Joseph L.

1991-01-01

Tritium and deuterium are separated from a gaseous mixture thereof, derived from a nuclear fusion reactor or some other source, by providing a casing with a bulk getter therein for absorbing the gaseous mixture to produce an initial loading of the getter, partially desorbing the getter to produce a desorbed mixture which is tritium-enriched, pumping the desorbed mixture into a separate container, the remaining gaseous loading in the getter being deuterium-enriched, desorbing the getter to a substantially greater extent to produce a deuterium-enriched gaseous mixture, and removing the deuterium-enriched mixture into another container. The bulk getter may comprise a zirconium-aluminum alloy, or a zirconium-vanadium-iron alloy. The partial desorption may reduce the loading by approximately fifty percent. The basic procedure may be extended to produce a multistage isotope separator, including at least one additional bulk getter into which the tritium-enriched mixture is absorbed. The second getter is then partially desorbed to produce a desorbed mixture which is further tritium-enriched. The last-mentioned mixture is then removed from the container for the second getter, which is then desorbed to a substantially greater extent to produce a desorbed mixture which is deuterium-enriched. The last-mentioned mixture is then removed so that the cycle can be continued and repeated. The method of isotope separation is also applicable to other hydrogen isotopes, in that the method can be employed for separating either deuterium or tritium from normal hydrogen.

Hydrogen isotope separation utilizing bulk getters

DOEpatents

Knize, Randall J.; Cecchi, Joseph L.

1990-01-01

Tritium and deuterium are separated from a gaseous mixture thereof, derived from a nuclear fusion reactor or some other source, by providing a casing with a bulk getter therein for absorbing the gaseous mixture to produce an initial loading of the getter, partially desorbing the getter to produce a desorbed mixture which is tritium-enriched, pumping the desorbed mixture into a separate container, the remaining gaseous loading in the getter being deuterium-enriched, desorbing the getter to a substantially greater extent to produce a deuterium-enriched gaseous mixture, and removing the deuterium-enriched mixture into another container. The bulk getter may comprise a zirconium-aluminum alloy, or a zirconium-vanadium-iron alloy. The partial desorption may reduce the loading by approximately fifty percent. The basic procedure may be extended to produce a multistage isotope separator, including at least one additional bulk getter into which the tritium-enriched mixture is absorbed. The second getter is then partially desorbed to produce a desorbed mixture which is further tritium-enriched. The last-mentioned mixture is then removed from the container for the second getter, which is then desorbed to a substantially greater extent to produce a desorbed mixture which is deuterium-enriched. The last-mentioned mixture is then removed so that the cycle can be continued and repeated. The method of isotope separation is also applicable to other hydrogen isotopes, in that the method can be employed for separating either deuterium or tritium from normal hydrogen.

Optimal design and experimental validation of a simulated moving bed chromatography for continuous recovery of formic acid in a model mixture of three organic acids from Actinobacillus bacteria fermentation.

PubMed

Park, Chanhun; Nam, Hee-Geun; Lee, Ki Bong; Mun, Sungyong

2014-10-24

The economically-efficient separation of formic acid from acetic acid and succinic acid has been a key issue in the production of formic acid with the Actinobacillus bacteria fermentation. To address this issue, an optimal three-zone simulated moving bed (SMB) chromatography for continuous separation of formic acid from acetic acid and succinic acid was developed in this study. As a first step for this task, the adsorption isotherm and mass-transfer parameters of each organic acid on the qualified adsorbent (Amberchrom-CG300C) were determined through a series of multiple frontal experiments. The determined parameters were then used in optimizing the SMB process for the considered separation. During such optimization, the additional investigation for selecting a proper SMB port configuration, which could be more advantageous for attaining better process performances, was carried out between two possible configurations. It was found that if the properly selected port configuration was adopted in the SMB of interest, the throughout and the formic-acid product concentration could be increased by 82% and 181% respectively. Finally, the optimized SMB process based on the properly selected port configuration was tested experimentally using a self-assembled SMB unit with three zones. The SMB experimental results and the relevant computer simulation verified that the developed process in this study was successful in continuous recovery of formic acid from a ternary organic-acid mixture of interest with high throughput, high purity, high yield, and high product concentration. Copyright © 2014 Elsevier B.V. All rights reserved.

Nonparametric Fine Tuning of Mixtures: Application to Non-Life Insurance Claims Distribution Estimation

NASA Astrophysics Data System (ADS)

Sardet, Laure; Patilea, Valentin

When pricing a specific insurance premium, actuary needs to evaluate the claims cost distribution for the warranty. Traditional actuarial methods use parametric specifications to model claims distribution, like lognormal, Weibull and Pareto laws. Mixtures of such distributions allow to improve the flexibility of the parametric approach and seem to be quite well-adapted to capture the skewness, the long tails as well as the unobserved heterogeneity among the claims. In this paper, instead of looking for a finely tuned mixture with many components, we choose a parsimonious mixture modeling, typically a two or three-component mixture. Next, we use the mixture cumulative distribution function (CDF) to transform data into the unit interval where we apply a beta-kernel smoothing procedure. A bandwidth rule adapted to our methodology is proposed. Finally, the beta-kernel density estimate is back-transformed to recover an estimate of the original claims density. The beta-kernel smoothing provides an automatic fine-tuning of the parsimonious mixture and thus avoids inference in more complex mixture models with many parameters. We investigate the empirical performance of the new method in the estimation of the quantiles with simulated nonnegative data and the quantiles of the individual claims distribution in a non-life insurance application.

Finite mixture modeling for vehicle crash data with application to hotspot identification.

PubMed

Park, Byung-Jung; Lord, Dominique; Lee, Chungwon

2014-10-01

The application of finite mixture regression models has recently gained an interest from highway safety researchers because of its considerable potential for addressing unobserved heterogeneity. Finite mixture models assume that the observations of a sample arise from two or more unobserved components with unknown proportions. Both fixed and varying weight parameter models have been shown to be useful for explaining the heterogeneity and the nature of the dispersion in crash data. Given the superior performance of the finite mixture model, this study, using observed and simulated data, investigated the relative performance of the finite mixture model and the traditional negative binomial (NB) model in terms of hotspot identification. For the observed data, rural multilane segment crash data for divided highways in California and Texas were used. The results showed that the difference measured by the percentage deviation in ranking orders was relatively small for this dataset. Nevertheless, the ranking results from the finite mixture model were considered more reliable than the NB model because of the better model specification. This finding was also supported by the simulation study which produced a high number of false positives and negatives when a mis-specified model was used for hotspot identification. Regarding an optimal threshold value for identifying hotspots, another simulation analysis indicated that there is a discrepancy between false discovery (increasing) and false negative rates (decreasing). Since the costs associated with false positives and false negatives are different, it is suggested that the selected optimal threshold value should be decided by considering the trade-offs between these two costs so that unnecessary expenses are minimized. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mathematical Model of Nonstationary Separation Processes Proceeding in the Cascade of Gas Centrifuges in the Process of Separation of Multicomponent Isotope Mixtures

NASA Astrophysics Data System (ADS)

Orlov, A. A.; Ushakov, A. A.; Sovach, V. P.

2017-03-01

We have developed and realized on software a mathematical model of the nonstationary separation processes proceeding in the cascades of gas centrifuges in the process of separation of multicomponent isotope mixtures. With the use of this model the parameters of the separation process of germanium isotopes have been calculated. It has been shown that the model adequately describes the nonstationary processes in the cascade and is suitable for calculating their parameters in the process of separation of multicomponent isotope mixtures.

A modified procedure for mixture-model clustering of regional geochemical data

USGS Publications Warehouse

Ellefsen, Karl J.; Smith, David B.; Horton, John D.

2014-01-01

A modified procedure is proposed for mixture-model clustering of regional-scale geochemical data. The key modification is the robust principal component transformation of the isometric log-ratio transforms of the element concentrations. This principal component transformation and the associated dimension reduction are applied before the data are clustered. The principal advantage of this modification is that it significantly improves the stability of the clustering. The principal disadvantage is that it requires subjective selection of the number of clusters and the number of principal components. To evaluate the efficacy of this modified procedure, it is applied to soil geochemical data that comprise 959 samples from the state of Colorado (USA) for which the concentrations of 44 elements are measured. The distributions of element concentrations that are derived from the mixture model and from the field samples are similar, indicating that the mixture model is a suitable representation of the transformed geochemical data. Each cluster and the associated distributions of the element concentrations are related to specific geologic and anthropogenic features. In this way, mixture model clustering facilitates interpretation of the regional geochemical data.

Different approaches in Partial Least Squares and Artificial Neural Network models applied for the analysis of a ternary mixture of Amlodipine, Valsartan and Hydrochlorothiazide

NASA Astrophysics Data System (ADS)

Darwish, Hany W.; Hassan, Said A.; Salem, Maissa Y.; El-Zeany, Badr A.

2014-03-01

Different chemometric models were applied for the quantitative analysis of Amlodipine (AML), Valsartan (VAL) and Hydrochlorothiazide (HCT) in ternary mixture, namely, Partial Least Squares (PLS) as traditional chemometric model and Artificial Neural Networks (ANN) as advanced model. PLS and ANN were applied with and without variable selection procedure (Genetic Algorithm GA) and data compression procedure (Principal Component Analysis PCA). The chemometric methods applied are PLS-1, GA-PLS, ANN, GA-ANN and PCA-ANN. The methods were used for the quantitative analysis of the drugs in raw materials and pharmaceutical dosage form via handling the UV spectral data. A 3-factor 5-level experimental design was established resulting in 25 mixtures containing different ratios of the drugs. Fifteen mixtures were used as a calibration set and the other ten mixtures were used as validation set to validate the prediction ability of the suggested methods. The validity of the proposed methods was assessed using the standard addition technique.

Flash-point prediction for binary partially miscible mixtures of flammable solvents.

PubMed

Liaw, Horng-Jang; Lu, Wen-Hung; Gerbaud, Vincent; Chen, Chan-Cheng

2008-05-30

Flash point is the most important variable used to characterize fire and explosion hazard of liquids. Herein, partially miscible mixtures are presented within the context of liquid-liquid extraction processes. This paper describes development of a model for predicting the flash point of binary partially miscible mixtures of flammable solvents. To confirm the predictive efficacy of the derived flash points, the model was verified by comparing the predicted values with the experimental data for the studied mixtures: methanol+octane; methanol+decane; acetone+decane; methanol+2,2,4-trimethylpentane; and, ethanol+tetradecane. Our results reveal that immiscibility in the two liquid phases should not be ignored in the prediction of flash point. Overall, the predictive results of this proposed model describe the experimental data well. Based on this evidence, therefore, it appears reasonable to suggest potential application for our model in assessment of fire and explosion hazards, and development of inherently safer designs for chemical processes containing binary partially miscible mixtures of flammable solvents.

40 CFR 790.3 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT (CONTINUED... purpose of this part: Act means the Toxic Substances Control Act, 15 U.S.C. 2601 et seq. Additive means a... data intended to show that two substances or mixtures are equivalent. Equivalent means that a chemical...

An on-line acoustic fluorocarbon coolant mixture analyzer for the ATLAS silicon tracker

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bates, R.; Battistin, M.; Berry, S.

2011-07-01

The ATLAS silicon tracker community foresees an upgrade from the present octafluoro-propane (C{sub 3}F{sub 8}) evaporative cooling fluid - to a composite fluid with a probable 10-20% admixture of hexafluoro-ethane (C{sub 2}F{sub 6}). Such a fluid will allow a lower evaporation temperature and will afford the tracker silicon substrates a better safety margin against leakage current-induced thermal runaway caused by cumulative radiation damage as the luminosity profile at the CERN Large Hadron Collider increases. Central to the use of this new fluid is a new custom-developed speed-of-sound instrument for continuous real-time measurement of the C{sub 3}F{sub 8}/C{sub 2}F{sub 6} mixturemore » ratio and flow. An acoustic vapour mixture analyzer/flow meter with new custom electronics allowing ultrasonic frequency transmission through gas mixtures has been developed for this application. Synchronous with the emission of an ultrasound 'chirp' from an acoustic transmitter, a fast readout clock (40 MHz) is started. The clock is stopped on receipt of an above threshold sound pulse at the receiver. Sound is alternately transmitted parallel and anti-parallel with the vapour flow for volume flow measurement from transducers that can serve as acoustic transmitters or receivers. In the development version, continuous real-time measurement of C{sub 3}F{sub 8}/C{sub 2}F{sub 6} flow and calculation of the mixture ratio is performed within a graphical user interface developed in PVSS-II, the Supervisory, Control and Data Acquisition standard chosen for LHC and its experiments at CERN. The described instrument has numerous potential applications - including refrigerant leak detection, the analysis of hydrocarbons, vapour mixtures for semiconductor manufacture and anesthetic gas mixtures. (authors)« less

Nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates of typical desert vegetation in western China.

PubMed

Ji, Cuicui; Jia, Yonghong; Gao, Zhihai; Wei, Huaidong; Li, Xiaosong

2017-01-01

Desert vegetation plays significant roles in securing the ecological integrity of oasis ecosystems in western China. Timely monitoring of photosynthetic/non-photosynthetic desert vegetation cover is necessary to guide management practices on land desertification and research into the mechanisms driving vegetation recession. In this study, nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates are investigated through comparing the performance of linear and nonlinear spectral mixture models with different endmembers applied to field spectral measurements of two types of typical desert vegetation, namely, Nitraria shrubs and Haloxylon. The main results were as follows. (1) The correct selection of endmembers is important for improving the accuracy of vegetation cover estimates, and in particular, shadow endmembers cannot be neglected. (2) For both the Nitraria shrubs and Haloxylon, the Kernel-based Nonlinear Spectral Mixture Model (KNSMM) with nonlinear parameters was the best unmixing model. In consideration of the computational complexity and accuracy requirements, the Linear Spectral Mixture Model (LSMM) could be adopted for Nitraria shrubs plots, but this will result in significant errors for the Haloxylon plots since the nonlinear spectral mixture effects were more obvious for this vegetation type. (3) The vegetation canopy structure (planophile or erectophile) determines the strength of the nonlinear spectral mixture effects. Therefore, no matter for Nitraria shrubs or Haloxylon, the non-linear spectral mixing effects between the photosynthetic / non-photosynthetic vegetation and the bare soil do exist, and its strength is dependent on the three-dimensional structure of the vegetation canopy. The choice of linear or nonlinear spectral mixture models is up to the consideration of computational complexity and the accuracy requirement.

Nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates of typical desert vegetation in western China

PubMed Central

Jia, Yonghong; Gao, Zhihai; Wei, Huaidong

2017-01-01

Desert vegetation plays significant roles in securing the ecological integrity of oasis ecosystems in western China. Timely monitoring of photosynthetic/non-photosynthetic desert vegetation cover is necessary to guide management practices on land desertification and research into the mechanisms driving vegetation recession. In this study, nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates are investigated through comparing the performance of linear and nonlinear spectral mixture models with different endmembers applied to field spectral measurements of two types of typical desert vegetation, namely, Nitraria shrubs and Haloxylon. The main results were as follows. (1) The correct selection of endmembers is important for improving the accuracy of vegetation cover estimates, and in particular, shadow endmembers cannot be neglected. (2) For both the Nitraria shrubs and Haloxylon, the Kernel-based Nonlinear Spectral Mixture Model (KNSMM) with nonlinear parameters was the best unmixing model. In consideration of the computational complexity and accuracy requirements, the Linear Spectral Mixture Model (LSMM) could be adopted for Nitraria shrubs plots, but this will result in significant errors for the Haloxylon plots since the nonlinear spectral mixture effects were more obvious for this vegetation type. (3) The vegetation canopy structure (planophile or erectophile) determines the strength of the nonlinear spectral mixture effects. Therefore, no matter for Nitraria shrubs or Haloxylon, the non-linear spectral mixing effects between the photosynthetic / non-photosynthetic vegetation and the bare soil do exist, and its strength is dependent on the three-dimensional structure of the vegetation canopy. The choice of linear or nonlinear spectral mixture models is up to the consideration of computational complexity and the accuracy requirement. PMID:29240777

Use of Computed X-ray Tomographic Data for Analyzing the Thermodynamics of a Dissociating Porous Sand/Hydrate Mixture

DOE R&D Accomplishments Database

Freifeld, Barry M.; Kneafsey, Timothy J.; Tomutsa, Liviu; Stern, Laura A.; Kirby, Stephen H.

2002-02-28

X-ray computed tomography (CT) is a method that has been used extensively in laboratory experiments for measuring rock properties and fluid transport behavior. More recently, CT scanning has been applied successfully to detect the presence and study the behavior of naturally occurring hydrates. In this study, we used a modified medical CT scanner to image and analyze the progression of a dissociation front in a synthetic methane hydrate/sand mixture. The sample was initially scanned under conditions at which the hydrate is stable (atmospheric pressure and liquid nitrogen temperature, 77 K). The end of the sample holder was then exposed to the ambient air, and the core was continuously scanned as dissociation occurred in response to the rising temperature. CT imaging captured the advancing dissociation front clearly and accurately. The evolved gas volume was monitored as a function of time. Measured by CT, the advancing hydrate dissociation front was modeled as a thermal conduction problem explicitly incorporating the enthalpy of dissociation, using the Stefan moving-boundary-value approach. The assumptions needed to perform the analysis consisted of temperatures at the model boundaries. The estimated value for thermal conductivity of 2.6 W/m K for the remaining water ice/sand mixture is higher than expected based on conduction alone; this high value may represent a lumped parameter that incorporates the processes of heat conduction, methane gas convection, and any kinetic effects that occur during dissociation. The technique presented here has broad implications for future laboratory and field testing that incorporates geophysical techniques to monitor gas hydrate dissociation.

Heat and mass transfer in a dissociated laminar boundary layer of air with consideration of the finite rate of chemical reaction

NASA Technical Reports Server (NTRS)

Oyegbesan, A. O.; Algermissen, J.

1986-01-01

A numerical investigation of heat and mass transfer in a dissociated laminar boundary layer of air on an isothermal flat plate is carried out for different degrees of cooling of the wall. A finite-difference chemical model is used to study elementary reactions involving NO2 and N2O. The analysis is based on equations of continuity, momentum, energy, conservation and state for the two-dimensional viscous flow of a reacting multicomponent mixtures. Attention is given to the effects of both catalyticity and noncatalyticity of the wall.

A hybrid pareto mixture for conditional asymmetric fat-tailed distributions.

PubMed

Carreau, Julie; Bengio, Yoshua

2009-07-01

In many cases, we observe some variables X that contain predictive information over a scalar variable of interest Y , with (X,Y) pairs observed in a training set. We can take advantage of this information to estimate the conditional density p(Y|X = x). In this paper, we propose a conditional mixture model with hybrid Pareto components to estimate p(Y|X = x). The hybrid Pareto is a Gaussian whose upper tail has been replaced by a generalized Pareto tail. A third parameter, in addition to the location and spread parameters of the Gaussian, controls the heaviness of the upper tail. Using the hybrid Pareto in a mixture model results in a nonparametric estimator that can adapt to multimodality, asymmetry, and heavy tails. A conditional density estimator is built by modeling the parameters of the mixture estimator as functions of X. We use a neural network to implement these functions. Such conditional density estimators have important applications in many domains such as finance and insurance. We show experimentally that this novel approach better models the conditional density in terms of likelihood, compared to competing algorithms: conditional mixture models with other types of components and a classical kernel-based nonparametric model.

Neurotoxicological and statistical analyses of a mixture of five organophosphorus pesticides using a ray design.

PubMed

Moser, V C; Casey, M; Hamm, A; Carter, W H; Simmons, J E; Gennings, C

2005-07-01

Environmental exposures generally involve chemical mixtures instead of single chemicals. Statistical models such as the fixed-ratio ray design, wherein the mixing ratio (proportions) of the chemicals is fixed across increasing mixture doses, allows for the detection and characterization of interactions among the chemicals. In this study, we tested for interaction(s) in a mixture of five organophosphorus (OP) pesticides (chlorpyrifos, diazinon, dimethoate, acephate, and malathion). The ratio of the five pesticides (full ray) reflected the relative dietary exposure estimates of the general population as projected by the US EPA Dietary Exposure Evaluation Model (DEEM). A second mixture was tested using the same dose levels of all pesticides, but excluding malathion (reduced ray). The experimental approach first required characterization of dose-response curves for the individual OPs to build a dose-additivity model. A series of behavioral measures were evaluated in adult male Long-Evans rats at the time of peak effect following a single oral dose, and then tissues were collected for measurement of cholinesterase (ChE) activity. Neurochemical (blood and brain cholinesterase [ChE] activity) and behavioral (motor activity, gait score, tail-pinch response score) endpoints were evaluated statistically for evidence of additivity. The additivity model constructed from the single chemical data was used to predict the effects of the pesticide mixture along the full ray (10-450 mg/kg) and the reduced ray (1.75-78.8 mg/kg). The experimental mixture data were also modeled and statistically compared to the additivity models. Analysis of the 5-OP mixture (the full ray) revealed significant deviation from additivity for all endpoints except tail-pinch response. Greater-than-additive responses (synergism) were observed at the lower doses of the 5-OP mixture, which contained non-effective dose levels of each of the components. The predicted effective doses (ED20, ED50) were about half that predicted by additivity, and for brain ChE and motor activity, there was a threshold shift in the dose-response curves. For the brain ChE and motor activity, there was no difference between the full (5-OP mixture) and reduced (4-OP mixture) rays, indicating that malathion did not influence the non-additivity. While the reduced ray for blood ChE showed greater deviation from additivity without malathion in the mixture, the non-additivity observed for the gait score was reversed when malathion was removed. Thus, greater-than-additive interactions were detected for both the full and reduced ray mixtures, and the role of malathion in the interactions varied depending on the endpoint. In all cases, the deviations from additivity occurred at the lower end of the dose-response curves.

Self-organising mixture autoregressive model for non-stationary time series modelling.

PubMed

Ni, He; Yin, Hujun

2008-12-01

Modelling non-stationary time series has been a difficult task for both parametric and nonparametric methods. One promising solution is to combine the flexibility of nonparametric models with the simplicity of parametric models. In this paper, the self-organising mixture autoregressive (SOMAR) network is adopted as a such mixture model. It breaks time series into underlying segments and at the same time fits local linear regressive models to the clusters of segments. In such a way, a global non-stationary time series is represented by a dynamic set of local linear regressive models. Neural gas is used for a more flexible structure of the mixture model. Furthermore, a new similarity measure has been introduced in the self-organising network to better quantify the similarity of time series segments. The network can be used naturally in modelling and forecasting non-stationary time series. Experiments on artificial, benchmark time series (e.g. Mackey-Glass) and real-world data (e.g. numbers of sunspots and Forex rates) are presented and the results show that the proposed SOMAR network is effective and superior to other similar approaches.

Numerical study of underwater dispersion of dilute and dense sediment-water mixtures

NASA Astrophysics Data System (ADS)

Chan, Ziying; Dao, Ho-Minh; Tan, Danielle S.

2018-05-01

As part of the nodule-harvesting process, sediment tailings are released underwater. Due to the long period of clouding in the water during the settling process, this presents a significant environmental and ecological concern. One possible solution is to release a mixture of sediment tailings and seawater, with the aim of reducing the settling duration as well as the amount of spreading. In this paper, we present some results of numerical simulations using the smoothed particle hydrodynamics (SPH) method to model the release of a fixed volume of pre-mixed sediment-water mixture into a larger body of quiescent water. Both the sediment-water mixture and the “clean” water are modeled as two different fluids, with concentration-dependent bulk properties of the sediment-water mixture adjusted according to the initial solids concentration. This numerical model was validated in a previous study, which indicated significant differences in the dispersion and settling process between dilute and dense mixtures, and that a dense mixture may be preferable. For this study, we investigate a wider range of volumetric concentration with the aim of determining the optimum volumetric concentration, as well as its overall effectiveness compared to the original process (100% sediment).

Cure models for estimating hospital-based breast cancer survival.

PubMed

Rama, Ranganathan; Swaminathan, Rajaraman; Venkatesan, Perumal

2010-01-01

Research on cancer survival is enriched by development and application of innovative analytical approaches in relation to standard methods. The aim of the present paper is to document the utility of a mixture model to estimate the cure fraction and compare it with other approaches. The data were for 1,107 patients with locally advanced breast cancer, who completed the neo-adjuvant treatment protocol during 1990-99 at the Cancer Institute (WIA), Chennai, India. Tumour stage, post-operative pathological node (PN) and tumour residue (TR) status were studied. Event free survival probability was estimated using the Kaplan-Meier method. Cure models under proportional and non-proportional hazard assumptions following log normal distribution for survival time were used to estimate both the cure fraction and the survival function for the uncured. Event free survival at 5 and 10 years were 64.2% and 52.6% respectively and cure fraction was 47.5% for all cases together. Follow up ranged between 0-15 years and survival probabilities showed minimal changes after 7 years of follow up. TR and PN emerged as independent prognostic factors using Cox and proportional hazard (PH) cure models. Proportionality condition was violated when tumour stage was considered and it was statistically significant only under PH and not under non PH cure models. However, TR and PN continued to be independent prognostic factors after adjusting for tumour stage using the non PH cure model. A consistent ordering of cure fractions with respect to factors of PN and TR was forthcoming across tumour stages using PH and non PH cure models, but perceptible differences in survival were observed between the two. If PH conditions are violated, analysis using a non PH model is advocated and mixture cure models are useful in estimating the cure fraction and constructing survival curves for non-cures.

Space-time variation of respiratory cancers in South Carolina: a flexible multivariate mixture modeling approach to risk estimation.

PubMed

Carroll, Rachel; Lawson, Andrew B; Kirby, Russell S; Faes, Christel; Aregay, Mehreteab; Watjou, Kevin

2017-01-01

Many types of cancer have an underlying spatiotemporal distribution. Spatiotemporal mixture modeling can offer a flexible approach to risk estimation via the inclusion of latent variables. In this article, we examine the application and benefits of using four different spatiotemporal mixture modeling methods in the modeling of cancer of the lung and bronchus as well as "other" respiratory cancer incidences in the state of South Carolina. Of the methods tested, no single method outperforms the other methods; which method is best depends on the cancer under consideration. The lung and bronchus cancer incidence outcome is best described by the univariate modeling formulation, whereas the "other" respiratory cancer incidence outcome is best described by the multivariate modeling formulation. Spatiotemporal multivariate mixture methods can aid in the modeling of cancers with small and sparse incidences when including information from a related, more common type of cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

Monitoring of herbal mixtures potentially containing synthetic cannabinoids as psychoactive compounds.

PubMed

Dresen, Sebastian; Ferreirós, Nerea; Pütz, Michael; Westphal, Folker; Zimmermann, Ralf; Auwärter, Volker

2010-10-01

Herbal mixtures like 'Spice' with potentially bioactive ingredients were available in many European countries since 2004 and are still widely used as a substitute for cannabis, although merchandized as 'herbal incense'. After gaining a high degree of popularity in 2008, big quantities of these drugs were sold. In December 2008, synthetic cannabinoids were identified in the mixtures which were not declared as ingredients: the C(8) homolog of the non-classical cannabinoid CP-47,497 (CP-47,497-C8) and a cannabimimetic aminoalkylindole called JWH-018. In February 2009, a few weeks after the German legislation put these compounds and further pharmacologically active homologs of CP-47,497 under control, another cannabinoid appeared in 'incense' products: the aminoalkylindole JWH-073. In this paper, the results of monitoring of commercially available 'incense' products from June 2008 to September 2009 are presented. In this period of time, more than 140 samples of herbal mixtures were analyzed for bioactive ingredients and synthetic cannabimimetic substances in particular. The results show that the composition of many products changed repeatedly over time as a reaction to prohibition and prosecution of resellers. Therefore neither the reseller nor the consumer of these mixtures can predict the actual content of the 'incense' products. As long as there is no possibility of generic definitions in the controlled substances legislation, further designer cannabinoids will appear on the market as soon as the next legal step has been taken. This is affirmed by the recent identification of the aminoalkylindoles JWH-250 and JWH-398. As further cannabinoids can be expected to occur in the near future, a continuous monitoring of these herbal mixtures is required. The identification of the synthetic opioid O-desmethyltramadol in a herbal mixture declared to contain 'kratom' proves that the concept of selling apparently natural products spiked with potentially dangerous synthetic chemicals/pharmaceuticals is a continuing trend on the market of 'legal highs'. Copyright © 2010 John Wiley & Sons, Ltd.

Impact of chemical proportions on the acute neurotoxicity of a mixture of seven carbamates in preweanling and adult rats.

PubMed

Moser, Virginia C; Padilla, Stephanie; Simmons, Jane Ellen; Haber, Lynne T; Hertzberg, Richard C

2012-09-01

Statistical design and environmental relevance are important aspects of studies of chemical mixtures, such as pesticides. We used a dose-additivity model to test experimentally the default assumptions of dose additivity for two mixtures of seven N-methylcarbamates (carbaryl, carbofuran, formetanate, methomyl, methiocarb, oxamyl, and propoxur). The best-fitting models were selected for the single-chemical dose-response data and used to develop a combined prediction model, which was then compared with the experimental mixture data. We evaluated behavioral (motor activity) and cholinesterase (ChE)-inhibitory (brain, red blood cells) outcomes at the time of peak acute effects following oral gavage in adult and preweanling (17 days old) Long-Evans male rats. The mixtures varied only in their mixing ratios. In the relative potency mixture, proportions of each carbamate were set at equitoxic component doses. A California environmental mixture was based on the 2005 sales of each carbamate in California. In adult rats, the relative potency mixture showed dose additivity for red blood cell ChE and motor activity, and brain ChE inhibition showed a modest greater-than additive (synergistic) response, but only at a middle dose. In rat pups, the relative potency mixture was either dose-additive (brain ChE inhibition, motor activity) or slightly less-than additive (red blood cell ChE inhibition). On the other hand, at both ages, the environmental mixture showed greater-than additive responses on all three endpoints, with significant deviations from predicted at most to all doses tested. Thus, we observed different interactive properties for different mixing ratios of these chemicals. These approaches for studying pesticide mixtures can improve evaluations of potential toxicity under varying experimental conditions that may mimic human exposures.

Conducting polymer networks synthesized by photopolymerization-induced phase separation

NASA Astrophysics Data System (ADS)

Yamashita, Yuki; Komori, Kana; Murata, Tasuku; Nakanishi, Hideyuki; Norisuye, Tomohisa; Yamao, Takeshi; Tran-Cong-Miyata, Qui

2018-03-01

Polymer mixtures composed of double networks of a polystyrene derivative (PSAF) and poly(methyl methacrylate) (PMMA) were alternatively synthesized by using ultraviolet (UV) and visible (Vis) light. The PSAF networks were generated by UV irradiation to photodimerize the anthracene (A) moieties labeled on the PSAF chains, whereas PMMA networks were produced by photopolymerization of methyl methacrylate (MMA) monomer and the cross-link reaction using ethylene glycol dimethacrylate (EGDMA) under Vis light irradiation. It was found that phase separation process of these networks can be independently induced and promptly controlled by using UV and Vis light. The characteristic length scale distribution of the resulting co-continuous morphology can be well regulated by the UV and Vis light intensity. In order to confirm and utilize the connectivity of the bicontinuous morphology observed by confocal microscopy, a very small amount, 0.1 wt%, of multi-walled carbon nanotubes (MWCNTs) was introduced into the mixture and the current-voltage (I-V) relationship was subsequently examined. Preliminary data show that MWCNTs are preferentially dispersed in the PSAF-rich continuous domains and the whole mixture became electrically conducting, confirming the connectivity of the observed bi-continuous morphology. The experimental data obtained in this study reveal a promising method to design various scaffolds for conducting soft matter taking advantages of photopolymerization-induced phase separation.

Piecewise Linear-Linear Latent Growth Mixture Models with Unknown Knots

ERIC Educational Resources Information Center

Kohli, Nidhi; Harring, Jeffrey R.; Hancock, Gregory R.

2013-01-01

Latent growth curve models with piecewise functions are flexible and useful analytic models for investigating individual behaviors that exhibit distinct phases of development in observed variables. As an extension of this framework, this study considers a piecewise linear-linear latent growth mixture model (LGMM) for describing segmented change of…

Dielectric relaxation and hydrogen bonding interaction in xylitol-water mixtures using time domain reflectometry

NASA Astrophysics Data System (ADS)

Rander, D. N.; Joshi, Y. S.; Kanse, K. S.; Kumbharkhane, A. C.

2016-01-01

The measurements of complex dielectric permittivity of xylitol-water mixtures have been carried out in the frequency range of 10 MHz-30 GHz using a time domain reflectometry technique. Measurements have been done at six temperatures from 0 to 25 °C and at different weight fractions of xylitol (0 < W X ≤ 0.7) in water. There are different models to explain the dielectric relaxation behaviour of binary mixtures, such as Debye, Cole-Cole or Cole-Davidson model. We have observed that the dielectric relaxation behaviour of binary mixtures of xylitol-water can be well described by Cole-Davidson model having an asymmetric distribution of relaxation times. The dielectric parameters such as static dielectric constant and relaxation time for the mixtures have been evaluated. The molecular interaction between xylitol and water molecules is discussed using the Kirkwood correlation factor ( g eff ) and thermodynamic parameter.

High voltage AC plasma torches with long electric arcs for plasma-chemical applications

NASA Astrophysics Data System (ADS)

Surov, A. V.; Popov, S. D.; Serba, E. O.; Pavlov, A. V.; Nakonechny, Gh V.; Spodobin, V. A.; Nikonov, A. V.; Subbotin, D. I.; Borovskoy, A. M.

2017-04-01

Powerful AC plasma torches are in demand for a number of advanced plasma chemical applications, they can provide high enthalpy of the working gas. IEE RAS specialists have developed a number of models of stationary thermal plasma torches for continuous operation on air with the power from 5 to 500 kW, and on mixture of H2O, CO2 and CH4 up to 150 kW. AC plasma torches were tested on the pilot plasmachemical installations. Powerful AC plasma torch with hollow electrodes and the gas vortex stabilization of arc in cylindrical channels and its operation characteristics are presented. Lifetime of its continuous operation on air is 2000 hours and thermal efficiency is about 92%, the electric arc length between two electrodes of the plasma torch exceeds 2 m.

Continuous and Batch Distillation in an Oldershaw Tray Column

ERIC Educational Resources Information Center

Silva, Carlos M.; Vaz, Raquel V.; Santiago, Ana S.; Lito, Patricia F.

2011-01-01

The importance of distillation in the separation field prompts the inclusion of distillation experiments in the chemical engineering curricula. This work describes the performance of an Oldershaw column in the rectification of a cyclohexane/n-heptane mixture. Total reflux distillation, continuous rectification under partial reflux, and batch…

CONTINUOUS MICRO-SORTING OF COMPLEX WASTE PLASTICS PARTICLEMIXTURES VIA LIQUID-FLUIDIZED BED CLASSIFICATION (LFBC) FOR WASTE MINIMIZATIONAND RECYCLING

EPA Science Inventory

A fundamental investigation is proposed to provide a technical basis for the development of a novel, liquid-fluidized bed classification (LFBC) technology for the continuous separation of complex waste plastic mixtures for in-process recycling and waste minimization. Although ...

Multi-stage Continuous Culture Fermentation of Glucose-Xylose Mixtures to Fuel Ethanol using Genetically Engineered Saccharomyces cerevisiae 424A

EPA Science Inventory

Multi-stage continuous (chemostat) culture fermentation (MCCF) with variable fermentor volumes was carried out to study utilizing glucose and xylose for ethanol production by means of mixed sugar fermentation (MSF). Variable fermentor volumes were used to enable enhanced sugar u...

Increasing Sensitivity In Continuous-Flow Electrophoresis

NASA Technical Reports Server (NTRS)

Sharnez, Rizwan; Sammons, David W.

1994-01-01

Sensitivity of continuous-flow electrophoresis (CFE) chamber increased by introducing lateral gradients in concentration of buffer solution and thickness of chamber. Such gradients, with resulting enhanced separation, achieved in CFE chamber with wedge-shaped cross section and collateral flow. Enables improved separations of homogeneous components of mixtures of variety of biologically important substances.

Broad Feshbach resonance in the 6Li-40K mixture.

PubMed

Tiecke, T G; Goosen, M R; Ludewig, A; Gensemer, S D; Kraft, S; Kokkelmans, S J J M F; Walraven, J T M

2010-02-05

We study the widths of interspecies Feshbach resonances in a mixture of the fermionic quantum gases 6Li and 40K. We develop a model to calculate the width and position of all available Feshbach resonances for a system. Using the model, we select the optimal resonance to study the {6}Li/{40}K mixture. Experimentally, we obtain the asymmetric Fano line shape of the interspecies elastic cross section by measuring the distillation rate of 6Li atoms from a potassium-rich 6Li/{40}K mixture as a function of magnetic field. This provides us with the first experimental determination of the width of a resonance in this mixture, DeltaB=1.5(5) G. Our results offer good perspectives for the observation of universal crossover physics using this mass-imbalanced fermionic mixture.

Coordinated Hard Sphere Mixture (CHaSM): A fast approximate model for oxide and silicate melts at extreme conditions

NASA Astrophysics Data System (ADS)

Wolf, A. S.; Asimow, P. D.; Stevenson, D. J.

2015-12-01

Recent first-principles calculations (e.g. Stixrude, 2009; de Koker, 2013), shock-wave experiments (Mosenfelder, 2009), and diamond-anvil cell investigations (Sanloup, 2013) indicate that silicate melts undergo complex structural evolution at high pressure. The observed increase in cation-coordination (e.g. Karki, 2006; 2007) induces higher compressibilities and lower adiabatic thermal gradients in melts as compared with their solid counterparts. These properties are crucial for understanding the evolution of impact-generated magma oceans, which are dominated by the poorly understood behavior of silicates at mantle pressures and temperatures (e.g. Stixrude et al. 2009). Probing these conditions is difficult for both theory and experiment, especially given the large compositional space (MgO-SiO2-FeO-Al2O3-etc). We develop a new model to understand and predict the behavior of oxide and silicate melts at extreme P-T conditions (Wolf et al., 2015). The Coordinated Hard Sphere Mixture (CHaSM) extends the Hard Sphere mixture model, accounting for the range of coordination states for each cation in the liquid. Using approximate analytic expressions for the hard sphere model, this fast statistical method compliments classical and first-principles methods, providing accurate thermodynamic and structural property predictions for melts. This framework is applied to the MgO system, where model parameters are trained on a collection of crystal polymorphs, producing realistic predictions of coordination evolution and the equation of state of MgO melt over a wide P-T range. Typical Mg-coordination numbers are predicted to evolve continuously from 5.25 (0 GPa) to 8.5 (250 GPa), comparing favorably with first-principles Molecular Dynamics (MD) simulations. We begin extending the model to a simplified mantle chemistry using empirical potentials (generally accurate over moderate pressure ranges, <~30 GPa), yielding predictions rooted in statistical representations of melt structure that compare well with more time-consuming classical MD calculations. This approach also sheds light on the universality of the increasing Grüneisen parameter trend for liquids (opposite that of solids), which directly reflects their progressive evolution toward more compact solid-like structures upon compression.

Nanomechanical characterization of heterogeneous and hierarchical biomaterials and tissues using nanoindentation: the role of finite mixture models.

PubMed

Zadpoor, Amir A

2015-03-01

Mechanical characterization of biological tissues and biomaterials at the nano-scale is often performed using nanoindentation experiments. The different constituents of the characterized materials will then appear in the histogram that shows the probability of measuring a certain range of mechanical properties. An objective technique is needed to separate the probability distributions that are mixed together in such a histogram. In this paper, finite mixture models (FMMs) are proposed as a tool capable of performing such types of analysis. Finite Gaussian mixture models assume that the measured probability distribution is a weighted combination of a finite number of Gaussian distributions with separate mean and standard deviation values. Dedicated optimization algorithms are available for fitting such a weighted mixture model to experimental data. Moreover, certain objective criteria are available to determine the optimum number of Gaussian distributions. In this paper, FMMs are used for interpreting the probability distribution functions representing the distributions of the elastic moduli of osteoarthritic human cartilage and co-polymeric microspheres. As for cartilage experiments, FMMs indicate that at least three mixture components are needed for describing the measured histogram. While the mechanical properties of the softer mixture components, often assumed to be associated with Glycosaminoglycans, were found to be more or less constant regardless of whether two or three mixture components were used, those of the second mixture component (i.e. collagen network) considerably changed depending on the number of mixture components. Regarding the co-polymeric microspheres, the optimum number of mixture components estimated by the FMM theory, i.e. 3, nicely matches the number of co-polymeric components used in the structure of the polymer. The computer programs used for the presented analyses are made freely available online for other researchers to use. Copyright © 2014 Elsevier B.V. All rights reserved.

Assessment of the Risks of Mixtures of Major Use Veterinary Antibiotics in European Surface Waters.

PubMed

Guo, Jiahua; Selby, Katherine; Boxall, Alistair B A

2016-08-02

Effects of single veterinary antibiotics on a range of aquatic organisms have been explored in many studies. In reality, surface waters will be exposed to mixtures of these substances. In this study, we present an approach for establishing risks of antibiotic mixtures to surface waters and illustrate this by assessing risks of mixtures of three major use antibiotics (trimethoprim, tylosin, and lincomycin) to algal and cyanobacterial species in European surface waters. Ecotoxicity tests were initially performed to assess the combined effects of the antibiotics to the cyanobacteria Anabaena flos-aquae. The results were used to evaluate two mixture prediction models: concentration addition (CA) and independent action (IA). The CA model performed best at predicting the toxicity of the mixture with the experimental 96 h EC50 for the antibiotic mixture being 0.248 μmol/L compared to the CA predicted EC50 of 0.21 μmol/L. The CA model was therefore used alongside predictions of exposure for different European scenarios and estimations of hazards obtained from species sensitivity distributions to estimate risks of mixtures of the three antibiotics. Risk quotients for the different scenarios ranged from 0.066 to 385 indicating that the combination of three substances could be causing adverse impacts on algal communities in European surface waters. This could have important implications for primary production and nutrient cycling. Tylosin contributed most to the risk followed by lincomycin and trimethoprim. While we have explored only three antibiotics, the combined experimental and modeling approach could readily be applied to the wider range of antibiotics that are in use.

Moving target detection method based on improved Gaussian mixture model

NASA Astrophysics Data System (ADS)

Ma, J. Y.; Jie, F. R.; Hu, Y. J.

2017-07-01

Gaussian Mixture Model is often employed to build background model in background difference methods for moving target detection. This paper puts forward an adaptive moving target detection algorithm based on improved Gaussian Mixture Model. According to the graylevel convergence for each pixel, adaptively choose the number of Gaussian distribution to learn and update background model. Morphological reconstruction method is adopted to eliminate the shadow.. Experiment proved that the proposed method not only has good robustness and detection effect, but also has good adaptability. Even for the special cases when the grayscale changes greatly and so on, the proposed method can also make outstanding performance.

Investigation of thermal and optical properties of some quartet mixed hydrogen-bonded liquid crystals

NASA Astrophysics Data System (ADS)

Okumuş, Mustafa

2017-11-01

In this study, the thermal and optical properties of quartet mixtures formed at different weight ratios (1:1:1:1 and 1.5:1:1:1) from liquid crystals 4-octyloxy-4‧-cyanobiphenyl (8OCB), 4-hexylbenzoic acid, 4-(octyloxy)benzoic acid and 4-(decyloxy)benzoic acid were investigated by differential scanning calorimeter (DSC) and polarized optic microscopy (POM). The phase transition temperatures of the novel quartet mixtures measured in the DSC experiments are in line with the POM experiments. The experimental results clearly show that the novel liquid crystal mixtures have displayed pure liquid crystalline properties. According to the phase diagram drawn from DSC results, the nematic range of the novel mixture at the eutectic point is larger than the nematic ranges of the components. The mesomorphic structures of produced homolog complex mixtures are found to be smectic and nematic phases. But the smectic phase cannot be observed in the novel complex 1.5:1:1:1 mixture during continuous cooling. The nematic range of the novel complex 1.5:1:1:1 mixture is bigger than the nematic range of the novel complex 1:1:1:1 mixture with increasing 8OCB. Also, the nematic-to-isotropic phase transition temperature decreases with increasing the weight ratio of 8OCB in the complex quartet mixture. Another interesting result is that the produced mixtures are to be like a medical cream at room temperatures. Furthermore, order parameter and thermal stability factor of the transitions are also calculated.

Mesoscale Modeling of LX-17 Under Isentropic Compression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Springer, H K; Willey, T M; Friedman, G

Mesoscale simulations of LX-17 incorporating different equilibrium mixture models were used to investigate the unreacted equation-of-state (UEOS) of TATB. Candidate TATB UEOS were calculated using the equilibrium mixture models and benchmarked with mesoscale simulations of isentropic compression experiments (ICE). X-ray computed tomography (XRCT) data provided the basis for initializing the simulations with realistic microstructural details. Three equilibrium mixture models were used in this study. The single constituent with conservation equations (SCCE) model was based on a mass-fraction weighted specific volume and the conservation of mass, momentum, and energy. The single constituent equation-of-state (SCEOS) model was based on a mass-fraction weightedmore » specific volume and the equation-of-state of the constituents. The kinetic energy averaging (KEA) model was based on a mass-fraction weighted particle velocity mixture rule and the conservation equations. The SCEOS model yielded the stiffest TATB EOS (0.121{micro} + 0.4958{micro}{sup 2} + 2.0473{micro}{sup 3}) and, when incorporated in mesoscale simulations of the ICE, demonstrated the best agreement with VISAR velocity data for both specimen thicknesses. The SCCE model yielded a relatively more compliant EOS (0.1999{micro}-0.6967{micro}{sup 2} + 4.9546{micro}{sup 3}) and the KEA model yielded the most compliant EOS (0.1999{micro}-0.6967{micro}{sup 2}+4.9546{micro}{sup 3}) of all the equilibrium mixture models. Mesoscale simulations with the lower density TATB adiabatic EOS data demonstrated the least agreement with VISAR velocity data.« less

Latent Transition Analysis with a Mixture Item Response Theory Measurement Model

ERIC Educational Resources Information Center

Cho, Sun-Joo; Cohen, Allan S.; Kim, Seock-Ho; Bottge, Brian

2010-01-01

A latent transition analysis (LTA) model was described with a mixture Rasch model (MRM) as the measurement model. Unlike the LTA, which was developed with a latent class measurement model, the LTA-MRM permits within-class variability on the latent variable, making it more useful for measuring treatment effects within latent classes. A simulation…

Activities of mixtures of soil-applied herbicides with different molecular targets.

PubMed

Kaushik, Shalini; Streibig, Jens Carl; Cedergreen, Nina

2006-11-01

The joint action of soil-applied herbicide mixtures with similar or different modes of action has been assessed by using the additive dose model (ADM). The herbicides chlorsulfuron, metsulfuron-methyl, pendimethalin and pretilachlor, applied either singly or in binary mixtures, were used on rice (Oryza sativa L.). The growth (shoot) response curves were described by a logistic dose-response model. The ED50 values and their corresponding standard errors obtained from the response curves were used to test statistically if the shape of the isoboles differed from the reference model (ADM). Results showed that mixtures of herbicides with similar molecular targets, i.e. chlorsulfuron and metsulfuron (acetolactate synthase (ALS) inhibitors), and with different molecular targets, i.e. pendimethalin (microtubule assembly inhibitor) and pretilachlor (very long chain fatty acids (VLCFAs) inhibitor), followed the ADM. Mixing herbicides with different molecular targets gave different results depending on whether pretilachlor or pendimethalin was involved. In general, mixtures of pretilachlor and sulfonylureas showed synergistic interactions, whereas mixtures of pendimethalin and sulfonylureas exhibited either antagonistic or additive activities. Hence, there is a large potential for both increasing the specificity of herbicides by using mixtures and lowering the total dose for weed control, while at the same time delaying the development of herbicide resistance by using mixtures with different molecular targets. Copyright (c) 2006 Society of Chemical Industry.

An EM-based semi-parametric mixture model approach to the regression analysis of competing-risks data.

PubMed

Ng, S K; McLachlan, G J

2003-04-15

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright 2003 John Wiley & Sons, Ltd.

Modeling Math Growth Trajectory--An Application of Conventional Growth Curve Model and Growth Mixture Model to ECLS K-5 Data

ERIC Educational Resources Information Center

Lu, Yi

2016-01-01

To model students' math growth trajectory, three conventional growth curve models and three growth mixture models are applied to the Early Childhood Longitudinal Study Kindergarten-Fifth grade (ECLS K-5) dataset in this study. The results of conventional growth curve model show gender differences on math IRT scores. When holding socio-economic…

Evaluating Differential Effects Using Regression Interactions and Regression Mixture Models

ERIC Educational Resources Information Center

Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung

2015-01-01

Research increasingly emphasizes understanding differential effects. This article focuses on understanding regression mixture models, which are relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their…

Numerical modeling and analytical modeling of cryogenic carbon capture in a de-sublimating heat exchanger

NASA Astrophysics Data System (ADS)

Yu, Zhitao; Miller, Franklin; Pfotenhauer, John M.

2017-12-01

Both a numerical and analytical model of the heat and mass transfer processes in a CO2, N2 mixture gas de-sublimating cross-flow finned duct heat exchanger system is developed to predict the heat transferred from a mixture gas to liquid nitrogen and the de-sublimating rate of CO2 in the mixture gas. The mixture gas outlet temperature, liquid nitrogen outlet temperature, CO2 mole fraction, temperature distribution and de-sublimating rate of CO2 through the whole heat exchanger was computed using both the numerical and analytic model. The numerical model is built using EES [1] (engineering equation solver). According to the simulation, a cross-flow finned duct heat exchanger can be designed and fabricated to validate the models. The performance of the heat exchanger is evaluated as functions of dimensionless variables, such as the ratio of the mass flow rate of liquid nitrogen to the mass flow rate of inlet flue gas.

Structure investigations on assembled astaxanthin molecules

NASA Astrophysics Data System (ADS)

Köpsel, Christian; Möltgen, Holger; Schuch, Horst; Auweter, Helmut; Kleinermanns, Karl; Martin, Hans-Dieter; Bettermann, Hans

2005-08-01

The carotenoid r,r-astaxanthin (3R,3‧R-dihydroxy-4,4‧-diketo-β-carotene) forms different types of aggregates in acetone-water mixtures. H-type aggregates were found in mixtures with a high part of water (e.g. 1:9 acetone-water mixture) whereas two different types of J-aggregates were identified in mixtures with a lower part of water (3:7 acetone-water mixture). These aggregates were characterized by recording UV/vis-absorption spectra, CD-spectra and fluorescence emissions. The sizes of the molecular assemblies were determined by dynamic light scattering experiments. The hydrodynamic diameter of the assemblies amounts 40 nm in 1:9 acetone-water mixtures and exceeds up to 1 μm in 3:7 acetone-water mixtures. Scanning tunneling microscopy monitored astaxanthin aggregates on graphite surfaces. The structure of the H-aggregate was obtained by molecular modeling calculations. The structure was confirmed by calculating the electronic absorption spectrum and the CD-spectrum where the molecular modeling structure was used as input.

Establishment method of a mixture model and its practical application for transmission gears in an engineering vehicle

NASA Astrophysics Data System (ADS)

Wang, Jixin; Wang, Zhenyu; Yu, Xiangjun; Yao, Mingyao; Yao, Zongwei; Zhang, Erping

2012-09-01

Highly versatile machines, such as wheel loaders, forklifts, and mining haulers, are subject to many kinds of working conditions, as well as indefinite factors that lead to the complexity of the load. The load probability distribution function (PDF) of transmission gears has many distributions centers; thus, its PDF cannot be well represented by just a single-peak function. For the purpose of representing the distribution characteristics of the complicated phenomenon accurately, this paper proposes a novel method to establish a mixture model. Based on linear regression models and correlation coefficients, the proposed method can be used to automatically select the best-fitting function in the mixture model. Coefficient of determination, the mean square error, and the maximum deviation are chosen and then used as judging criteria to describe the fitting precision between the theoretical distribution and the corresponding histogram of the available load data. The applicability of this modeling method is illustrated by the field testing data of a wheel loader. Meanwhile, the load spectra based on the mixture model are compiled. The comparison results show that the mixture model is more suitable for the description of the load-distribution characteristics. The proposed research improves the flexibility and intelligence of modeling, reduces the statistical error and enhances the fitting accuracy, and the load spectra complied by this method can better reflect the actual load characteristic of the gear component.

Compact determination of hydrogen isotopes

DOE PAGES

Robinson, David

2017-04-06

Scanning calorimetry of a confined, reversible hydrogen sorbent material has been previously proposed as a method to determine compositions of unknown mixtures of diatomic hydrogen isotopologues and helium. Application of this concept could result in greater process knowledge during the handling of these gases. Previously published studies have focused on mixtures that do not include tritium. This paper focuses on modeling to predict the effect of tritium in mixtures of the isotopologues on a calorimetry scan. Furthermore, the model predicts that tritium can be measured with a sensitivity comparable to that observed for hydrogen-deuterium mixtures, and that under so memore » conditions, it may be possible to determine the atomic fractions of all three isotopes in a gas mixture.« less

Analyzing repeated measures semi-continuous data, with application to an alcohol dependence study.

PubMed

Liu, Lei; Strawderman, Robert L; Johnson, Bankole A; O'Quigley, John M

2016-02-01

Two-part random effects models (Olsen and Schafer,(1) Tooze et al.(2)) have been applied to repeated measures of semi-continuous data, characterized by a mixture of a substantial proportion of zero values and a skewed distribution of positive values. In the original formulation of this model, the natural logarithm of the positive values is assumed to follow a normal distribution with a constant variance parameter. In this article, we review and consider three extensions of this model, allowing the positive values to follow (a) a generalized gamma distribution, (b) a log-skew-normal distribution, and (c) a normal distribution after the Box-Cox transformation. We allow for the possibility of heteroscedasticity. Maximum likelihood estimation is shown to be conveniently implemented in SAS Proc NLMIXED. The performance of the methods is compared through applications to daily drinking records in a secondary data analysis from a randomized controlled trial of topiramate for alcohol dependence treatment. We find that all three models provide a significantly better fit than the log-normal model, and there exists strong evidence for heteroscedasticity. We also compare the three models by the likelihood ratio tests for non-nested hypotheses (Vuong(3)). The results suggest that the generalized gamma distribution provides the best fit, though no statistically significant differences are found in pairwise model comparisons. © The Author(s) 2012.

Continuous Probabilistic Modeling of Tracer Stone Dispersal in Upper Regime

NASA Astrophysics Data System (ADS)

Hernandez Moreira, R. R.; Viparelli, E.

2017-12-01

Morphodynamic models that specifically account for the non-uniformity of the bed material are generally based on some form of the active layer approximation. These models have proven to be useful tools in the study of transport, erosion and deposition of non-uniform bed material in the case of channel bed aggradation and degradation. However, when local spatial effects over short time scales compared to those characterizing the changes in mean bed elevation dominate the vertical sediment fluxes, as is the presence of bedforms, active layer models cannot capture key details of the sediment transport process. To overcome the limitations of active layer based models, Parker, Paola and Leclair (PPL) proposed a continuous probabilistic modeling frameworks in which the sediment exchange between the bedload transport and the mobile bed is described in terms of probability density functions of bed elevation, entrainment and deposition. Here we present the implementation of a modified version of the PPL modeling framework for the study of tracer stones dispsersal in upper regime bedload transport conditions (i.e. upper regime plane bed at the transition between dunes and antidunes, downstream migrating antidunes and upper regime plane bed with bedload transport in sheet flow mode) in which the probability functions are based on measured time series of bed elevation fluctuations. The extension to the more general case of mixtures of sediments differing in size is the future development of the proposed work.

Lattice model for water-solute mixtures.

PubMed

Furlan, A P; Almarza, N G; Barbosa, M C

2016-10-14

A lattice model for the study of mixtures of associating liquids is proposed. Solvent and solute are modeled by adapting the associating lattice gas (ALG) model. The nature of interaction of solute/solvent is controlled by tuning the energy interactions between the patches of ALG model. We have studied three set of parameters, resulting in, hydrophilic, inert, and hydrophobic interactions. Extensive Monte Carlo simulations were carried out, and the behavior of pure components and the excess properties of the mixtures have been studied. The pure components, water (solvent) and solute, have quite similar phase diagrams, presenting gas, low density liquid, and high density liquid phases. In the case of solute, the regions of coexistence are substantially reduced when compared with both the water and the standard ALG models. A numerical procedure has been developed in order to attain series of results at constant pressure from simulations of the lattice gas model in the grand canonical ensemble. The excess properties of the mixtures, volume and enthalpy as the function of the solute fraction, have been studied for different interaction parameters of the model. Our model is able to reproduce qualitatively well the excess volume and enthalpy for different aqueous solutions. For the hydrophilic case, we show that the model is able to reproduce the excess volume and enthalpy of mixtures of small alcohols and amines. The inert case reproduces the behavior of large alcohols such as propanol, butanol, and pentanol. For the last case (hydrophobic), the excess properties reproduce the behavior of ionic liquids in aqueous solution.

Diagnostic evaluations of microwave generated helium and nitrogen plasma mixtures

NASA Technical Reports Server (NTRS)

Haraburda, Scott S.; Hawley, Martin C.; Dinkel, Duane W.

1990-01-01

The goal of this work is to continue the development to fundamentally understand the plasma processes as applied to spacecraft propulsion. The diagnostic experiments used are calorimetric, dimensional, and spectroscopic measurements using the TM 011 and TM 012 modes in the resonance cavity. These experimental techniques are highly important in furthering the understanding of plasma phenomena and of designing rocket thrusters. Several experimental results are included using nitrogen and helium gas mixtures.

Approximation of the breast height diameter distribution of two-cohort stands by mixture models III Kernel density estimators vs mixture models

Treesearch

Rafal Podlaski; Francis A. Roesch

2014-01-01

Two-component mixtures of either the Weibull distribution or the gamma distribution and the kernel density estimator were used for describing the diameter at breast height (dbh) empirical distributions of two-cohort stands. The data consisted of study plots from the Å wietokrzyski National Park (central Poland) and areas close to and including the North Carolina section...

The nonlinear model for emergence of stable conditions in gas mixture in force field

NASA Astrophysics Data System (ADS)

Kalutskov, Oleg; Uvarova, Liudmila

2016-06-01

The case of M-component liquid evaporation from the straight cylindrical capillary into N - component gas mixture in presence of external forces was reviewed. It is assumed that the gas mixture is not ideal. The stable states in gas phase can be formed during the evaporation process for the certain model parameter valuesbecause of the mass transfer initial equationsnonlinearity. The critical concentrations of the resulting gas mixture components (the critical component concentrations at which the stable states occur in mixture) were determined mathematically for the case of single-component fluid evaporation into two-component atmosphere. It was concluded that this equilibrium concentration ratio of the mixture components can be achieved by external force influence on the mass transfer processes. It is one of the ways to create sustainable gas clusters that can be used effectively in modern nanotechnology.

A general mixture theory. I. Mixtures of spherical molecules

NASA Astrophysics Data System (ADS)

Hamad, Esam Z.

1996-08-01

We present a new general theory for obtaining mixture properties from the pure species equations of state. The theory addresses the composition and the unlike interactions dependence of mixture equation of state. The density expansion of the mixture equation gives the exact composition dependence of all virial coefficients. The theory introduces multiple-index parameters that can be calculated from binary unlike interaction parameters. In this first part of the work, details are presented for the first and second levels of approximations for spherical molecules. The second order model is simple and very accurate. It predicts the compressibility factor of additive hard spheres within simulation uncertainty (equimolar with size ratio of three). For nonadditive hard spheres, comparison with compressibility factor simulation data over a wide range of density, composition, and nonadditivity parameter, gave an average error of 2%. For mixtures of Lennard-Jones molecules, the model predictions are better than the Weeks-Chandler-Anderson perturbation theory.

Bayesian mixture modeling of significant p values: A meta-analytic method to estimate the degree of contamination from H₀.

PubMed

Gronau, Quentin Frederik; Duizer, Monique; Bakker, Marjan; Wagenmakers, Eric-Jan

2017-09-01

Publication bias and questionable research practices have long been known to corrupt the published record. One method to assess the extent of this corruption is to examine the meta-analytic collection of significant p values, the so-called p -curve (Simonsohn, Nelson, & Simmons, 2014a). Inspired by statistical research on false-discovery rates, we propose a Bayesian mixture model analysis of the p -curve. Our mixture model assumes that significant p values arise either from the null-hypothesis H ₀ (when their distribution is uniform) or from the alternative hypothesis H1 (when their distribution is accounted for by a simple parametric model). The mixture model estimates the proportion of significant results that originate from H ₀, but it also estimates the probability that each specific p value originates from H ₀. We apply our model to 2 examples. The first concerns the set of 587 significant p values for all t tests published in the 2007 volumes of Psychonomic Bulletin & Review and the Journal of Experimental Psychology: Learning, Memory, and Cognition; the mixture model reveals that p values higher than about .005 are more likely to stem from H ₀ than from H ₁. The second example concerns 159 significant p values from studies on social priming and 130 from yoked control studies. The results from the yoked controls confirm the findings from the first example, whereas the results from the social priming studies are difficult to interpret because they are sensitive to the prior specification. To maximize accessibility, we provide a web application that allows researchers to apply the mixture model to any set of significant p values. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Optimization of β-casein stabilized nanoemulsions using experimental mixture design.

PubMed

Maher, Patrick G; Fenelon, Mark A; Zhou, Yankun; Kamrul Haque, Md; Roos, Yrjö H

2011-10-01

The objective of this study was to determine the effect of changing viscosity and glass transition temperature in the continuous phase of nanoemulsion systems on subsequent stability. Formulations comprising of β-casein (2.5%, 5%, 7.5%, and 10% w/w), lactose (0% to 20% w/w), and trehalose (0% to 20% w/w) were generated from Design of Experiments (DOE) software and tested for glass transition temperature and onset of ice-melting temperature in maximally freeze-concentrated state (T(g) ' & T(m) '), and viscosity (μ). Increasing β-casein content resulted in significant (P < 0.0001) increases in viscosity and T(m) ' (P= 0.0003), and significant (P < 0.0001) decreases in T(g) '. A mixture design was used to predict the optimum levels of lactose and trehalose required to attain the minimum and maximum T(g) ' and viscosity in solution at fixed protein contents. These mixtures were used to form the continuous phase of β-casein stabilized nanoemulsions (10% w/w sunflower oil) prepared by microfluidization at 70 MPa. Nanoemulsions were analyzed for T(g) ' & T(m) ', as well as viscosity, mean particle size, and stability. Increasing levels of β-casein (2.5% to 10% w/w) resulted in a significant (P < 0.0001) increase in viscosity (5 to 156 mPa.s), significant increase in particle size (P= 0.0115) from 186 to 199 nm, and significant decrease (P= 0.0001) in T(g) ' (-45 to -50 °C). Increasing the protein content resulted in a significant (P < 0.0001) increase in nanoemulsion stability. A mixture DOE was successfully used to predict glass transition and rheological properties for development of a continuous phase for use in nanoemulsions. © 2011 Institute of Food Technologists®

Decomposition of heterogeneous organic matterand its long-term stabilization in soils

USGS Publications Warehouse

Sierra, Carlos A.; Harmon, Mark E.; Perakis, Steven S.

2011-01-01

Soil organic matter is a complex mixture of material with heterogeneous biological, physical, and chemical properties. Decomposition models represent this heterogeneity either as a set of discrete pools with different residence times or as a continuum of qualities. It is unclear though, whether these two different approaches yield comparable predictions of organic matter dynamics. Here, we compare predictions from these two different approaches and propose an intermediate approach to study organic matter decomposition based on concepts from continuous models implemented numerically. We found that the disagreement between discrete and continuous approaches can be considerable depending on the degree of nonlinearity of the model and simulation time. The two approaches can diverge substantially for predicting long-term processes in soils. Based on our alternative approach, which is a modification of the continuous quality theory, we explored the temporal patterns that emerge by treating substrate heterogeneity explicitly. The analysis suggests that the pattern of carbon mineralization over time is highly dependent on the degree and form of nonlinearity in the model, mostly expressed as differences in microbial growth and efficiency for different substrates. Moreover, short-term stabilization and destabilization mechanisms operating simultaneously result in long-term accumulation of carbon characterized by low decomposition rates, independent of the characteristics of the incoming litter. We show that representation of heterogeneity in the decomposition process can lead to substantial improvements in our understanding of carbon mineralization and its long-term stability in soils.

Thermodynamics of concentrated electrolyte mixtures and the prediction of mineral solubilities to high temperatures for mixtures in the system Na-K-Mg-Cl-SO 4-OH-H 2O

NASA Astrophysics Data System (ADS)

Pabalan, Roberto T.; Pitzer, Kenneth S.

1987-09-01

Mineral solubilities in binary and ternary electrolyte mixtures in the system Na-K-Mg-Cl-SO 4-OH-H 2O are calculated to high temperatures using available thermodynamic data for solids and for aqueous electrolyte solutions. Activity and osmotic coefficients are derived from the ion-interaction model of Pitzer (1973, 1979) and co-workers, the parameters of which are evaluated from experimentally determined solution properties or from solubility data in binary and ternary mixtures. Excellent to good agreement with experimental solubilities for binary and ternary mixtures indicate that the model can be successfully used to predict mineral-solution equilibria to high temperatures. Although there are currently no theoretical forms for the temperature dependencies of the various model parameters, the solubility data in ternary mixtures can be adequately represented by constant values of the mixing term θ ij and values of ψ ijk which are either constant or have a simple temperature dependence. Since no additional parameters are needed to describe the thermodynamic properties of more complex electrolyte mixtures, the calculations can be extended to equilibrium studies relevant to natural systems. Examples of predicted solubilities are given for the quaternary system NaCl-KCl-MgCl 2-H 2O.

Lattice Boltzmann scheme for mixture modeling: analysis of the continuum diffusion regimes recovering Maxwell-Stefan model and incompressible Navier-Stokes equations.

PubMed

Asinari, Pietro

2009-11-01

A finite difference lattice Boltzmann scheme for homogeneous mixture modeling, which recovers Maxwell-Stefan diffusion model in the continuum limit, without the restriction of the mixture-averaged diffusion approximation, was recently proposed [P. Asinari, Phys. Rev. E 77, 056706 (2008)]. The theoretical basis is the Bhatnagar-Gross-Krook-type kinetic model for gas mixtures [P. Andries, K. Aoki, and B. Perthame, J. Stat. Phys. 106, 993 (2002)]. In the present paper, the recovered macroscopic equations in the continuum limit are systematically investigated by varying the ratio between the characteristic diffusion speed and the characteristic barycentric speed. It comes out that the diffusion speed must be at least one order of magnitude (in terms of Knudsen number) smaller than the barycentric speed, in order to recover the Navier-Stokes equations for mixtures in the incompressible limit. Some further numerical tests are also reported. In particular, (1) the solvent and dilute test cases are considered, because they are limiting cases in which the Maxwell-Stefan model reduces automatically to Fickian cases. Moreover, (2) some tests based on the Stefan diffusion tube are reported for proving the complete capabilities of the proposed scheme in solving Maxwell-Stefan diffusion problems. The proposed scheme agrees well with the expected theoretical results.

Support vector regression and artificial neural network models for stability indicating analysis of mebeverine hydrochloride and sulpiride mixtures in pharmaceutical preparation: A comparative study

NASA Astrophysics Data System (ADS)

Naguib, Ibrahim A.; Darwish, Hany W.

2012-02-01

A comparison between support vector regression (SVR) and Artificial Neural Networks (ANNs) multivariate regression methods is established showing the underlying algorithm for each and making a comparison between them to indicate the inherent advantages and limitations. In this paper we compare SVR to ANN with and without variable selection procedure (genetic algorithm (GA)). To project the comparison in a sensible way, the methods are used for the stability indicating quantitative analysis of mixtures of mebeverine hydrochloride and sulpiride in binary mixtures as a case study in presence of their reported impurities and degradation products (summing up to 6 components) in raw materials and pharmaceutical dosage form via handling the UV spectral data. For proper analysis, a 6 factor 5 level experimental design was established resulting in a training set of 25 mixtures containing different ratios of the interfering species. An independent test set consisting of 5 mixtures was used to validate the prediction ability of the suggested models. The proposed methods (linear SVR (without GA) and linear GA-ANN) were successfully applied to the analysis of pharmaceutical tablets containing mebeverine hydrochloride and sulpiride mixtures. The results manifest the problem of nonlinearity and how models like the SVR and ANN can handle it. The methods indicate the ability of the mentioned multivariate calibration models to deconvolute the highly overlapped UV spectra of the 6 components' mixtures, yet using cheap and easy to handle instruments like the UV spectrophotometer.

A Mixtures-of-Trees Framework for Multi-Label Classification

PubMed Central

Hong, Charmgil; Batal, Iyad; Hauskrecht, Milos

2015-01-01

We propose a new probabilistic approach for multi-label classification that aims to represent the class posterior distribution P(Y|X). Our approach uses a mixture of tree-structured Bayesian networks, which can leverage the computational advantages of conditional tree-structured models and the abilities of mixtures to compensate for tree-structured restrictions. We develop algorithms for learning the model from data and for performing multi-label predictions using the learned model. Experiments on multiple datasets demonstrate that our approach outperforms several state-of-the-art multi-label classification methods. PMID:25927011

Liquid class predictor for liquid handling of complex mixtures

DOEpatents

Seglke, Brent W [San Ramon, CA; Lekin, Timothy P [Livermore, CA

2008-12-09

A method of establishing liquid classes of complex mixtures for liquid handling equipment. The mixtures are composed of components and the equipment has equipment parameters. The first step comprises preparing a response curve for the components. The next step comprises using the response curve to prepare a response indicator for the mixtures. The next step comprises deriving a model that relates the components and the mixtures to establish the liquid classes.

Regression mixture models: Does modeling the covariance between independent variables and latent classes improve the results?

PubMed Central

Lamont, Andrea E.; Vermunt, Jeroen K.; Van Horn, M. Lee

2016-01-01

Regression mixture models are increasingly used as an exploratory approach to identify heterogeneity in the effects of a predictor on an outcome. In this simulation study, we test the effects of violating an implicit assumption often made in these models – i.e., independent variables in the model are not directly related to latent classes. Results indicated that the major risk of failing to model the relationship between predictor and latent class was an increase in the probability of selecting additional latent classes and biased class proportions. Additionally, this study tests whether regression mixture models can detect a piecewise relationship between a predictor and outcome. Results suggest that these models are able to detect piecewise relations, but only when the relationship between the latent class and the predictor is included in model estimation. We illustrate the implications of making this assumption through a re-analysis of applied data examining heterogeneity in the effects of family resources on academic achievement. We compare previous results (which assumed no relation between independent variables and latent class) to the model where this assumption is lifted. Implications and analytic suggestions for conducting regression mixture based on these findings are noted. PMID:26881956

A Concentration Addition Model to Assess Activation of the Pregnane X Receptor (PXR) by Pesticide Mixtures Found in the French Diet

PubMed Central

de Sousa, Georges; Nawaz, Ahmad; Cravedi, Jean-Pierre; Rahmani, Roger

2014-01-01

French consumers are exposed to mixtures of pesticide residues in part through food consumption. As a xenosensor, the pregnane X receptor (hPXR) is activated by numerous pesticides, the combined effect of which is currently unknown. We examined the activation of hPXR by seven pesticide mixtures most likely found in the French diet and their individual components. The mixture's effect was estimated using the concentration addition (CA) model. PXR transactivation was measured by monitoring luciferase activity in hPXR/HepG2 cells and CYP3A4 expression in human hepatocytes. The three mixtures with the highest potency were evaluated using the CA model, at equimolar concentrations and at their relative proportion in the diet. The seven mixtures significantly activated hPXR and induced the expression of CYP3A4 in human hepatocytes. Of the 14 pesticides which constitute the three most active mixtures, four were found to be strong hPXR agonists, four medium, and six weak. Depending on the mixture and pesticide proportions, additive, greater than additive or less than additive effects between compounds were demonstrated. Predictions of the combined effects were obtained with both real-life and equimolar proportions at low concentrations. Pesticides act mostly additively to activate hPXR, when present in a mixture. Modulation of hPXR activation and its target genes induction may represent a risk factor contributing to exacerbate the physiological response of the hPXR signaling pathways and to explain some adverse effects in humans. PMID:25028461

Panic disorder and its subtypes: a comprehensive analysis of panic symptom heterogeneity using epidemiological and treatment seeking samples

PubMed Central

Roberson-Nay, R.; Kendler, K. S.

2014-01-01

Background Panic disorder (PD) is a heterogeneous syndrome that can present with a variety of symptom profiles that potentially reflect distinct etiologic pathways. The present study represents the most comprehensive examination of phenotypic variance in PD with and without agoraphobia for the purpose of identifying clinically relevant and etiologically meaningful subtypes. Method Latent class (LC) and factor mixture analysis were used to examine panic symptom data ascertained from three national epidemiologic surveys [Epidemiological Catchment Area (ECA), National Comorbidity Study (NCS), National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), Wave 1], a twin study [Virginia Adult Twin Study of Psychiatric and Substance Use Disorders (VATSPSUD)] and a clinical trial (Cross-National Collaborative Panic Study [CNCPS]). Results Factor mixture models (versus LC) generally provided better fit to panic symptom data and suggested two panic classes for the ECA, VATSPSUD and CNCPS, with one class typified by prominent respiratory symptoms. The NCS yielded two classes, but suggested both qualitative and quantitative differences. The more contemporary NESARC sample supported a two and three class model, with the three class model suggesting two variants of respiratory panic. The NESARC’s three class model continued to provide the best fit when the model was restricted to a more severe form of PD/panic disorder with agoraphobia. Conclusions Results from epidemiologic and clinical samples suggest two panic subtypes, with one subtype characterized by a respiratory component and a second class typified by general somatic symptoms. Results are discussed in light of their relevance to the etiopathogenesis of PD. PMID:21557895

On the multiple imputation variance estimator for control-based and delta-adjusted pattern mixture models.

PubMed

Tang, Yongqiang

2017-12-01

Control-based pattern mixture models (PMM) and delta-adjusted PMMs are commonly used as sensitivity analyses in clinical trials with non-ignorable dropout. These PMMs assume that the statistical behavior of outcomes varies by pattern in the experimental arm in the imputation procedure, but the imputed data are typically analyzed by a standard method such as the primary analysis model. In the multiple imputation (MI) inference, Rubin's variance estimator is generally biased when the imputation and analysis models are uncongenial. One objective of the article is to quantify the bias of Rubin's variance estimator in the control-based and delta-adjusted PMMs for longitudinal continuous outcomes. These PMMs assume the same observed data distribution as the mixed effects model for repeated measures (MMRM). We derive analytic expressions for the MI treatment effect estimator and the associated Rubin's variance in these PMMs and MMRM as functions of the maximum likelihood estimator from the MMRM analysis and the observed proportion of subjects in each dropout pattern when the number of imputations is infinite. The asymptotic bias is generally small or negligible in the delta-adjusted PMM, but can be sizable in the control-based PMM. This indicates that the inference based on Rubin's rule is approximately valid in the delta-adjusted PMM. A simple variance estimator is proposed to ensure asymptotically valid MI inferences in these PMMs, and compared with the bootstrap variance. The proposed method is illustrated by the analysis of an antidepressant trial, and its performance is further evaluated via a simulation study. © 2017, The International Biometric Society.

Transient Catalytic Combustor Model With Detailed Gas and Surface Chemistry

NASA Technical Reports Server (NTRS)

Struk, Peter M.; Dietrich, Daniel L.; Mellish, Benjamin P.; Miller, Fletcher J.; Tien, James S.

2005-01-01

In this work, we numerically investigate the transient combustion of a premixed gas mixture in a narrow, perfectly-insulated, catalytic channel which can represent an interior channel of a catalytic monolith. The model assumes a quasi-steady gas-phase and a transient, thermally thin solid phase. The gas phase is one-dimensional, but it does account for heat and mass transfer in a direction perpendicular to the flow via appropriate heat and mass transfer coefficients. The model neglects axial conduction in both the gas and in the solid. The model includes both detailed gas-phase reactions and catalytic surface reactions. The reactants modeled so far include lean mixtures of dry CO and CO/H2 mixtures, with pure oxygen as the oxidizer. The results include transient computations of light-off and system response to inlet condition variations. In some cases, the model predicts two different steady-state solutions depending on whether the channel is initially hot or cold. Additionally, the model suggests that the catalytic ignition of CO/O2 mixtures is extremely sensitive to small variations of inlet equivalence ratios and parts per million levels of H2.

Using dynamic N-mixture models to test cavity limitation on northern flying squirrel demographic parameters using experimental nest box supplementation.

PubMed

Priol, Pauline; Mazerolle, Marc J; Imbeau, Louis; Drapeau, Pierre; Trudeau, Caroline; Ramière, Jessica

2014-06-01

Dynamic N-mixture models have been recently developed to estimate demographic parameters of unmarked individuals while accounting for imperfect detection. We propose an application of the Dail and Madsen (2011: Biometrics, 67, 577-587) dynamic N-mixture model in a manipulative experiment using a before-after control-impact design (BACI). Specifically, we tested the hypothesis of cavity limitation of a cavity specialist species, the northern flying squirrel, using nest box supplementation on half of 56 trapping sites. Our main purpose was to evaluate the impact of an increase in cavity availability on flying squirrel population dynamics in deciduous stands in northwestern Québec with the dynamic N-mixture model. We compared abundance estimates from this recent approach with those from classic capture-mark-recapture models and generalized linear models. We compared apparent survival estimates with those from Cormack-Jolly-Seber (CJS) models. Average recruitment rate was 6 individuals per site after 4 years. Nevertheless, we found no effect of cavity supplementation on apparent survival and recruitment rates of flying squirrels. Contrary to our expectations, initial abundance was not affected by conifer basal area (food availability) and was negatively affected by snag basal area (cavity availability). Northern flying squirrel population dynamics are not influenced by cavity availability at our deciduous sites. Consequently, we suggest that this species should not be considered an indicator of old forest attributes in our study area, especially in view of apparent wide population fluctuations across years. Abundance estimates from N-mixture models were similar to those from capture-mark-recapture models, although the latter had greater precision. Generalized linear mixed models produced lower abundance estimates, but revealed the same relationship between abundance and snag basal area. Apparent survival estimates from N-mixture models were higher and less precise than those from CJS models. However, N-mixture models can be particularly useful to evaluate management effects on animal populations, especially for species that are difficult to detect in situations where individuals cannot be uniquely identified. They also allow investigating the effects of covariates at the site level, when low recapture rates would require restricting classic CMR analyses to a subset of sites with the most captures.

Fabrication of a novel superhydrophobic and superoleophilic surface by one-step electrodeposition method for continuous oil/water separation

NASA Astrophysics Data System (ADS)

Xiang, Meisu; Jiang, Meihuizi; Zhang, Yanzong; Liu, Yan; Shen, Fei; Yang, Gang; He, Yan; Wang, Lilin; Zhang, Xiaohong; Deng, Shihuai

2018-03-01

A novel superhydrophobic and superoleophilic surface was fabricated by one-step electrodeposition on stainless steel meshes, and the durability and oil/water separation properties were assessed. Field emission scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), fourier transform infrared spectroscopy (FT-IR) and optical contact angle measurements were used to characterize surface morphologies, chemical compositions, and wettabilities, respectively. The results indicated that the as-prepared mesh preformed excellent superhydrophobicity and superoleophilicity with a high water contact angle (WCA) of 162 ± 1° and oil contact angle of (OCA) 0°. Meanwhile, the as-prepared mesh also exhibited continuous separation capacity of many kinds of oil/water mixtures, and the separation efficiency for lubrication oil/water mixture was about 98.6%. In addition, after 10 separation cycles, the as-prepared mesh possessed the WCAs of 155 ± 2°, the OCAs of 0° and the separation efficiency of 97.8% for lubrication oil/water mixtures. The as-prepared mesh also retained superhydrophobic and superoleophilic properties after abrading, immersing in salt solutions and different pH solutions.

Eco-Friendly Superwetting Material for Highly Effective Separations of Oil/Water Mixtures and Oil-in-Water Emulsions.

PubMed

Wang, Chih-Feng; Yang, Sheng-Yi; Kuo, Shiao-Wei

2017-02-20

Because the treatment of oily wastewater, generated from many industrial processes, has become an increasing environmental concern, the search continues for simple, inexpensive, eco-friendly, and readily scalable processes for fabricating novel materials capable of effective oil/water separation. In this study we prepared an eco-friendly superhydrophilic and underwater superoleophobic polyvinylpyrrolidone (PVP)-modified cotton that mediated extremely efficient separations of mixtures of oil/water and oil/corrosive solutions. This PVP-modified cotton exhibited excellent antifouling properties and could be used to separate oil/water mixtures continuously for up to 20 h. Moreover, the compressed PVP-modified cotton could separate both surfactant-free and -stabilized oil-in-water emulsions with fluxes of up to 23,500 L m -2 h -1 bar -1 -a level one to two orders of magnitude higher than that possible when using traditional ultrafiltration membranes having similar rejection properties. The high performance of our PVP-modified cotton and its green, low-energy, cost-effective preparation suggest its great potential for practical applications.

Eco-Friendly Superwetting Material for Highly Effective Separations of Oil/Water Mixtures and Oil-in-Water Emulsions

NASA Astrophysics Data System (ADS)

Wang, Chih-Feng; Yang, Sheng-Yi; Kuo, Shiao-Wei

2017-02-01

Because the treatment of oily wastewater, generated from many industrial processes, has become an increasing environmental concern, the search continues for simple, inexpensive, eco-friendly, and readily scalable processes for fabricating novel materials capable of effective oil/water separation. In this study we prepared an eco-friendly superhydrophilic and underwater superoleophobic polyvinylpyrrolidone (PVP)-modified cotton that mediated extremely efficient separations of mixtures of oil/water and oil/corrosive solutions. This PVP-modified cotton exhibited excellent antifouling properties and could be used to separate oil/water mixtures continuously for up to 20 h. Moreover, the compressed PVP-modified cotton could separate both surfactant-free and -stabilized oil-in-water emulsions with fluxes of up to 23,500 L m-2 h-1 bar-1—a level one to two orders of magnitude higher than that possible when using traditional ultrafiltration membranes having similar rejection properties. The high performance of our PVP-modified cotton and its green, low-energy, cost-effective preparation suggest its great potential for practical applications.

Eco-Friendly Superwetting Material for Highly Effective Separations of Oil/Water Mixtures and Oil-in-Water Emulsions

PubMed Central

Wang, Chih-Feng; Yang, Sheng-Yi; Kuo, Shiao-Wei

2017-01-01

Because the treatment of oily wastewater, generated from many industrial processes, has become an increasing environmental concern, the search continues for simple, inexpensive, eco-friendly, and readily scalable processes for fabricating novel materials capable of effective oil/water separation. In this study we prepared an eco-friendly superhydrophilic and underwater superoleophobic polyvinylpyrrolidone (PVP)-modified cotton that mediated extremely efficient separations of mixtures of oil/water and oil/corrosive solutions. This PVP-modified cotton exhibited excellent antifouling properties and could be used to separate oil/water mixtures continuously for up to 20 h. Moreover, the compressed PVP-modified cotton could separate both surfactant-free and -stabilized oil-in-water emulsions with fluxes of up to 23,500 L m−2 h−1 bar−1—a level one to two orders of magnitude higher than that possible when using traditional ultrafiltration membranes having similar rejection properties. The high performance of our PVP-modified cotton and its green, low-energy, cost-effective preparation suggest its great potential for practical applications. PMID:28216617

Spurious Latent Classes in the Mixture Rasch Model

ERIC Educational Resources Information Center

Alexeev, Natalia; Templin, Jonathan; Cohen, Allan S.

2011-01-01

Mixture Rasch models have been used to study a number of psychometric issues such as goodness of fit, response strategy differences, strategy shifts, and multidimensionality. Although these models offer the potential for improving understanding of the latent variables being measured, under some conditions overextraction of latent classes may…

Individual and binary toxicity of anatase and rutile nanoparticles towards Ceriodaphnia dubia.

PubMed

Iswarya, V; Bhuvaneshwari, M; Chandrasekaran, N; Mukherjee, Amitava

2016-09-01

Increasing usage of engineered nanoparticles, especially Titanium dioxide (TiO2) in various commercial products has necessitated their toxicity evaluation and risk assessment, especially in the aquatic ecosystem. In the present study, a comprehensive toxicity assessment of anatase and rutile NPs (individual as well as a binary mixture) has been carried out in a freshwater matrix on Ceriodaphnia dubia under different irradiation conditions viz., visible and UV-A. Anatase and rutile NPs produced an LC50 of about 37.04 and 48mg/L, respectively, under visible irradiation. However, lesser LC50 values of about 22.56 (anatase) and 23.76 (rutile) mg/L were noted under UV-A irradiation. A toxic unit (TU) approach was followed to determine the concentrations of binary mixtures of anatase and rutile. The binary mixture resulted in an antagonistic and additive effect under visible and UV-A irradiation, respectively. Among the two different modeling approaches used in the study, Marking-Dawson model was noted to be a more appropriate model than Abbott model for the toxicity evaluation of binary mixtures. The agglomeration of NPs played a significant role in the induction of antagonistic and additive effects by the mixture based on the irradiation applied. TEM and zeta potential analysis confirmed the surface interactions between anatase and rutile NPs in the mixture. Maximum uptake was noticed at 0.25 total TU of the binary mixture under visible irradiation and 1 TU of anatase NPs for UV-A irradiation. Individual NPs showed highest uptake under UV-A than visible irradiation. In contrast, binary mixture showed a difference in the uptake pattern based on the type of irradiation exposed. Copyright © 2016 Elsevier B.V. All rights reserved.

Rasch Mixture Models for DIF Detection: A Comparison of Old and New Score Specifications

ERIC Educational Resources Information Center

Frick, Hannah; Strobl, Carolin; Zeileis, Achim

2015-01-01

Rasch mixture models can be a useful tool when checking the assumption of measurement invariance for a single Rasch model. They provide advantages compared to manifest differential item functioning (DIF) tests when the DIF groups are only weakly correlated with the manifest covariates available. Unlike in single Rasch models, estimation of Rasch…

Modeling biofiltration of VOC mixtures under steady-state conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baltzis, B.C.; Wojdyla, S.M.; Zarook, S.M.

1997-06-01

Treatment of air streams contaminated with binary volatile organic compound (VOC) mixtures in classical biofilters under steady-state conditions of operation was described with a general mathematical model. The model accounts for potential kinetic interactions among the pollutants, effects of oxygen availability on biodegradation, and biomass diversification in the filter bed. While the effects of oxygen were always taken into account, two distinct cases were considered for the experimental model validation. The first involves kinetic interactions, but no biomass differentiation, used for describing data from biofiltration of benzene/toluene mixtures. The second case assumes that each pollutant is treated by a differentmore » type of biomass. Each biomass type is assumed to form separate patches of biofilm on the solid packing material, thus kinetic interference does not occur. This model was used for describing biofiltration of ethanol/butanol mixtures. Experiments were performed with classical biofilters packed with mixtures of peat moss and perlite (2:3, volume:volume). The model equations were solved through the use of computer codes based on the fourth-order Runge-Kutta technique for the gas-phase mass balances and the method of orthogonal collocation for the concentration profiles in the biofilms. Good agreement between model predictions and experimental data was found in almost all cases. Oxygen was found to be extremely important in the case of polar VOCs (ethanol/butanol).« less

Avoidance in hypochondriasis.

PubMed

Doherty-Torstrick, Emily R; Walton, Kate E; Barsky, Arthur J; Fallon, Brian A

2016-10-01

The DSM-5 diagnosis of illness anxiety disorder adds avoidance as a component of a behavioral response to illness fears - one that was not present in prior DSM criteria of hypochondriasis. However, maladaptive avoidance as a necessary or useful criterion has yet to be empirically supported. 195 individuals meeting DSM-IV criteria for hypochondriasis based on structured interview completed a variety of self-report and clinician-administered assessments. Data on maladaptive avoidance were obtained using the six-item subscale of the clinician-administered Hypochondriasis - Yale Brown Obsessive Compulsive Scale - Modified. To determine if avoidance emerged as a useful indicator in hypochondriasis, we compared the relative fit of continuous latent trait, categorical latent class, and hybrid factor mixture models. A two-class factor mixture model fit the data best, with Class 1 (n=147) exhibiting a greater level of severity of avoidance than Class 2 (n=48). The more severely avoidant group was found to have higher levels of hypochondriacal symptom severity, functional impairment, and anxiety, as well as lower quality of life. These results suggest that avoidance may be a valid behavioral construct and a useful component of the new diagnostic criteria of illness anxiety in the DSM-5, with implications for somatic symptom disorder. Copyright © 2016 Elsevier Inc. All rights reserved.

Species and temperature measurements of methane oxidation in a nanosecond repetitively pulsed discharge

PubMed Central

Lefkowitz, Joseph K; Guo, Peng; Rousso, Aric; Ju, Yiguang

2015-01-01

Speciation and temperature measurements of methane oxidation during a nanosecond repetitively pulsed discharge in a low-temperature flow reactor have been performed. Measurements of temperature and formaldehyde during a burst of pulses were made on a time-dependent basis using tunable diode laser absorption spectroscopy, and measurements of all other major stable species were made downstream of a continuously pulsed discharge using gas chromatography. The major species for a stoichiometric methane/oxygen/helium mixture with 75% dilution are H2O, CO, CO2, H2, CH2O, CH3OH, C2H6, C2H4 and C2H2. A modelling tool to simulate homogeneous plasma combustion kinetics is assembled by combining the ZDPlasKin and CHEMKIN codes. In addition, a kinetic model for plasma-assisted combustion (HP-Mech/plasma) of methane, oxygen and helium mixtures has been assembled to simulate the measurements. Predictions can accurately capture reactant consumption as well as production of the major product species. However, significant disagreement is found for minor species, particularly CH2O and CH3OH. Further analysis revealed that the plasma-activated low-temperature oxidation pathways, particularly those involving CH3O2 radical reactions and methane reactions with O(1D), are responsible for this disagreement. PMID:26170433

Epileptic Seizure Detection Based on Time-Frequency Images of EEG Signals using Gaussian Mixture Model and Gray Level Co-Occurrence Matrix Features.

PubMed

Li, Yang; Cui, Weigang; Luo, Meilin; Li, Ke; Wang, Lina

2018-01-25

The electroencephalogram (EEG) signal analysis is a valuable tool in the evaluation of neurological disorders, which is commonly used for the diagnosis of epileptic seizures. This paper presents a novel automatic EEG signal classification method for epileptic seizure detection. The proposed method first employs a continuous wavelet transform (CWT) method for obtaining the time-frequency images (TFI) of EEG signals. The processed EEG signals are then decomposed into five sub-band frequency components of clinical interest since these sub-band frequency components indicate much better discriminative characteristics. Both Gaussian Mixture Model (GMM) features and Gray Level Co-occurrence Matrix (GLCM) descriptors are then extracted from these sub-band TFI. Additionally, in order to improve classification accuracy, a compact feature selection method by combining the ReliefF and the support vector machine-based recursive feature elimination (RFE-SVM) algorithm is adopted to select the most discriminative feature subset, which is an input to the SVM with the radial basis function (RBF) for classifying epileptic seizure EEG signals. The experimental results from a publicly available benchmark database demonstrate that the proposed approach provides better classification accuracy than the recently proposed methods in the literature, indicating the effectiveness of the proposed method in the detection of epileptic seizures.

Modeling the soil water retention curves of soil-gravel mixtures with regression method on the Loess Plateau of China.

PubMed

Wang, Huifang; Xiao, Bo; Wang, Mingyu; Shao, Ming'an

2013-01-01

Soil water retention parameters are critical to quantify flow and solute transport in vadose zone, while the presence of rock fragments remarkably increases their variability. Therefore a novel method for determining water retention parameters of soil-gravel mixtures is required. The procedure to generate such a model is based firstly on the determination of the quantitative relationship between the content of rock fragments and the effective saturation of soil-gravel mixtures, and then on the integration of this relationship with former analytical equations of water retention curves (WRCs). In order to find such relationships, laboratory experiments were conducted to determine WRCs of soil-gravel mixtures obtained with a clay loam soil mixed with shale clasts or pebbles in three size groups with various gravel contents. Data showed that the effective saturation of the soil-gravel mixtures with the same kind of gravels within one size group had a linear relation with gravel contents, and had a power relation with the bulk density of samples at any pressure head. Revised formulas for water retention properties of the soil-gravel mixtures are proposed to establish the water retention curved surface models of the power-linear functions and power functions. The analysis of the parameters obtained by regression and validation of the empirical models showed that they were acceptable by using either the measured data of separate gravel size group or those of all the three gravel size groups having a large size range. Furthermore, the regression parameters of the curved surfaces for the soil-gravel mixtures with a large range of gravel content could be determined from the water retention data of the soil-gravel mixtures with two representative gravel contents or bulk densities. Such revised water retention models are potentially applicable in regional or large scale field investigations of significantly heterogeneous media, where various gravel sizes and different gravel contents are present.

Modeling the Soil Water Retention Curves of Soil-Gravel Mixtures with Regression Method on the Loess Plateau of China

PubMed Central

Wang, Huifang; Xiao, Bo; Wang, Mingyu; Shao, Ming'an

2013-01-01

Soil water retention parameters are critical to quantify flow and solute transport in vadose zone, while the presence of rock fragments remarkably increases their variability. Therefore a novel method for determining water retention parameters of soil-gravel mixtures is required. The procedure to generate such a model is based firstly on the determination of the quantitative relationship between the content of rock fragments and the effective saturation of soil-gravel mixtures, and then on the integration of this relationship with former analytical equations of water retention curves (WRCs). In order to find such relationships, laboratory experiments were conducted to determine WRCs of soil-gravel mixtures obtained with a clay loam soil mixed with shale clasts or pebbles in three size groups with various gravel contents. Data showed that the effective saturation of the soil-gravel mixtures with the same kind of gravels within one size group had a linear relation with gravel contents, and had a power relation with the bulk density of samples at any pressure head. Revised formulas for water retention properties of the soil-gravel mixtures are proposed to establish the water retention curved surface models of the power-linear functions and power functions. The analysis of the parameters obtained by regression and validation of the empirical models showed that they were acceptable by using either the measured data of separate gravel size group or those of all the three gravel size groups having a large size range. Furthermore, the regression parameters of the curved surfaces for the soil-gravel mixtures with a large range of gravel content could be determined from the water retention data of the soil-gravel mixtures with two representative gravel contents or bulk densities. Such revised water retention models are potentially applicable in regional or large scale field investigations of significantly heterogeneous media, where various gravel sizes and different gravel contents are present. PMID:23555040

Phenomenological Modeling and Laboratory Simulation of Long-Term Aging of Asphalt Mixtures

NASA Astrophysics Data System (ADS)

Elwardany, Michael Dawoud

The accurate characterization of asphalt mixture properties as a function of pavement service life is becoming more important as more powerful pavement design and performance prediction methods are implemented. Oxidative aging is a major distress mechanism of asphalt pavements. Aging increases the stiffness and brittleness of the material, which leads to a high cracking potential. Thus, an improved understanding of the aging phenomenon and its effect on asphalt binder chemical and rheological properties will allow for the prediction of mixture properties as a function of pavement service life. Many researchers have conducted laboratory binder thin-film aging studies; however, this approach does not allow for studying the physicochemical effects of mineral fillers on age hardening rates in asphalt mixtures. Moreover, aging phenomenon in the field is governed by kinetics of binder oxidation, oxygen diffusion through mastic phase, and oxygen percolation throughout the air voids structure. In this study, laboratory aging trials were conducted on mixtures prepared using component materials of several field projects throughout the USA and Canada. Laboratory aged materials were compared against field cores sampled at different ages. Results suggested that oven aging of loose mixture at 95°C is the most promising laboratory long-term aging method. Additionally, an empirical model was developed in order to account for the effect of mineral fillers on age hardening rates in asphalt mixtures. Kinetics modeling was used to predict field aging levels throughout pavement thickness and to determine the required laboratory aging duration to match field aging. Kinetics model outputs are calibrated using measured data from the field to account for the effects of oxygen diffusion and percolation. Finally, the calibrated model was validated using independent set of field sections. This work is expected to provide basis for improved asphalt mixture and pavement design procedures in order to save taxpayers' money.

An Innovative Concept for Testing Rutting Susceptibility of Asphalt Mixture

NASA Astrophysics Data System (ADS)

Mohseni, Alaeddin; Azari, Haleh

Currently, flow number (FN) is being used for measuring permanent deformation resistance of asphalt mixtures. The provisional AASHTO TP 79-10 test method specifies the requirements of the FN test; however, there are undefined levels of test variables, such as temperature, axial stress, and confinement. Therefore, agreeable FN criteria that can reliably discriminate between various mixtures have not been established yet. As the asphalt industry continues to develop more sophisticated mixtures (Warm Mix, RAP and RAS), the FN value has failed to capture the true complexity of the asphalt mixtures. These shortcomings and the unpredictable testing time of the FN test have affected its usefulness for evaluating high temperature performance of asphalt mixtures. A new test procedure for evaluation of rutting susceptibility of asphalt mixtures is being proposed. The new procedure is conducted at one temperature and multiple stresses on the same replicate in three increments of 500 cycles, which only takes 33 minutes to complete. The property of the test is the permanent strain due to the last cycle of each test increment (Minimum Strain Rate, or MSR). A master curve is developed by plotting the MSR values versus parameter TP, which is a product of Temperature and Pressure. The MSR master curve represents the unit rutting damage (rut per axle) of asphalt mixtures at any stress and temperature and can be used in laboratory for material characterization, mix design verification, ranking of the mixtures, or for pavement design applications to predict rut depth for project climate and design traffic.

High electrical resistivity Nd-Fe-B die-upset magnet doped with eutectic DyF3-LiF salt mixture

NASA Astrophysics Data System (ADS)

Kim, K. M.; Kim, J. Y.; Kwon, H. W.; Kim, D. H.; Lee, J. G.; Yu, J. H.

2017-05-01

Nd-Fe-B-type die-upset magnet with high electrical resistivity was prepared by doping of eutectic DyF3-LiF salt mixture. Mixture of melt-spun Nd-Fe-B flakes (MQU-F: Nd13.6Fe73.6Co6.6Ga0.6B5.6) and eutectic binary (DyF3-LiF) salt (25 mol% DyF3 - 75 mol% LiF) was hot-pressed and then die-upset. By adding the eutectic salt mixture (> 4 wt%), electrical resistivity of the die-upset magnet was enhanced to over 400 μ Ω .cm compared to 190 μ Ω .cm of the un-doped magnet. Remarkable enhancement of the electrical resistivity was attributed to homogeneous and continuous coverage of the interface between flakes by the easily melted eutectic salt dielectric mixture. It was revealed that active substitution of the Nd atoms in neighboring flakes by the Dy atoms from the added (DyF3-LiF) salt mixture had occurred during such a quick thermal processing of hot-pressing and die-upsetting. This Dy substitution led to coercivity enhancement in the die-upset magnet doped with the eutectic (DyF3-LiF) salt mixture. Coercivity and remanence of the die-upset magnet doped with (DyF3-LiF) salt mixture was as good as those of the DyF3-doped magnet.

Automatic Control of the Concrete Mixture Homogeneity in Cycling Mixers

NASA Astrophysics Data System (ADS)

Anatoly Fedorovich, Tikhonov; Drozdov, Anatoly

2018-03-01

The article describes the factors affecting the concrete mixture quality related to the moisture content of aggregates, since the effectiveness of the concrete mixture production is largely determined by the availability of quality management tools at all stages of the technological process. It is established that the unaccounted moisture of aggregates adversely affects the concrete mixture homogeneity and, accordingly, the strength of building structures. A new control method and the automatic control system of the concrete mixture homogeneity in the technological process of mixing components have been proposed, since the tasks of providing a concrete mixture are performed by the automatic control system of processing kneading-and-mixing machinery with operational automatic control of homogeneity. Theoretical underpinnings of the control of the mixture homogeneity are presented, which are related to a change in the frequency of vibrodynamic vibrations of the mixer body. The structure of the technical means of the automatic control system for regulating the supply of water is determined depending on the change in the concrete mixture homogeneity during the continuous mixing of components. The following technical means for establishing automatic control have been chosen: vibro-acoustic sensors, remote terminal units, electropneumatic control actuators, etc. To identify the quality indicator of automatic control, the system offers a structure flowchart with transfer functions that determine the ACS operation in transient dynamic mode.

Kinetics of methane production from the codigestion of switchgrass and Spirulina platensis algae.

PubMed

El-Mashad, Hamed M

2013-03-01

Anaerobic batch digestion of four feedstocks was conducted at 35 and 50 °C: switchgrass; Spirulina platensis algae; and two mixtures of both switchgrass and S. platensis. Mixture 1 was composed of 87% switchgrass (based on volatile solids) and 13% S. platensis. Mixture 2 was composed of 67% switchgrass and 33% S. platensis. The kinetics of methane production from these feedstocks was studied using four first order models: exponential, Gompertz, Fitzhugh, and Cone. The methane yields after 40days of digestion at 35 °C were 355, 127, 143 and 198 ml/g VS, respectively for S. platensis, switchgrass, and Mixtures 1 and 2, while the yields at 50 °C were 358, 167, 198, and 236 ml/g VS, respectively. Based on Akaike's information criterion, the Cone model best described the experimental data. The Cone model was validated with experimental data collected from the digestion of a third mixture that was composed of 83% switchgrass and 17% S. platensis. Published by Elsevier Ltd.

Advanced stability indicating chemometric methods for quantitation of amlodipine and atorvastatin in their quinary mixture with acidic degradation products

NASA Astrophysics Data System (ADS)

Darwish, Hany W.; Hassan, Said A.; Salem, Maissa Y.; El-Zeany, Badr A.

2016-02-01

Two advanced, accurate and precise chemometric methods are developed for the simultaneous determination of amlodipine besylate (AML) and atorvastatin calcium (ATV) in the presence of their acidic degradation products in tablet dosage forms. The first method was Partial Least Squares (PLS-1) and the second was Artificial Neural Networks (ANN). PLS was compared to ANN models with and without variable selection procedure (genetic algorithm (GA)). For proper analysis, a 5-factor 5-level experimental design was established resulting in 25 mixtures containing different ratios of the interfering species. Fifteen mixtures were used as calibration set and the other ten mixtures were used as validation set to validate the prediction ability of the suggested models. The proposed methods were successfully applied to the analysis of pharmaceutical tablets containing AML and ATV. The methods indicated the ability of the mentioned models to solve the highly overlapped spectra of the quinary mixture, yet using inexpensive and easy to handle instruments like the UV-VIS spectrophotometer.

Thermal conductivity of disperse insulation materials and their mixtures

NASA Astrophysics Data System (ADS)

Geža, V.; Jakovičs, A.; Gendelis, S.; Usiļonoks, I.; Timofejevs, J.

2017-10-01

Development of new, more efficient thermal insulation materials is a key to reduction of heat losses and contribution to greenhouse gas emissions. Two innovative materials developed at Thermeko LLC are Izoprok and Izopearl. This research is devoted to experimental study of thermal insulation properties of both materials as well as their mixture. Results show that mixture of 40% Izoprok and 60% of Izopearl has lower thermal conductivity than pure materials. In this work, material thermal conductivity dependence temperature is also measured. Novel modelling approach is used to model spatial distribution of disperse insulation material. Computational fluid dynamics approach is also used to estimate role of different heat transfer phenomena in such porous mixture. Modelling results show that thermal convection plays small role in heat transfer despite large fraction of air within material pores.

A comparative study of mixture cure models with covariate

NASA Astrophysics Data System (ADS)

Leng, Oh Yit; Khalid, Zarina Mohd

2017-05-01

In survival analysis, the survival time is assumed to follow a non-negative distribution, such as the exponential, Weibull, and log-normal distributions. In some cases, the survival time is influenced by some observed factors. The absence of these observed factors may cause an inaccurate estimation in the survival function. Therefore, a survival model which incorporates the influences of observed factors is more appropriate to be used in such cases. These observed factors are included in the survival model as covariates. Besides that, there are cases where a group of individuals who are cured, that is, not experiencing the event of interest. Ignoring the cure fraction may lead to overestimate in estimating the survival function. Thus, a mixture cure model is more suitable to be employed in modelling survival data with the presence of a cure fraction. In this study, three mixture cure survival models are used to analyse survival data with a covariate and a cure fraction. The first model includes covariate in the parameterization of the susceptible individuals survival function, the second model allows the cure fraction to depend on covariate, and the third model incorporates covariate in both cure fraction and survival function of susceptible individuals. This study aims to compare the performance of these models via a simulation approach. Therefore, in this study, survival data with varying sample sizes and cure fractions are simulated and the survival time is assumed to follow the Weibull distribution. The simulated data are then modelled using the three mixture cure survival models. The results show that the three mixture cure models are more appropriate to be used in modelling survival data with the presence of cure fraction and an observed factor.

Metal-Polycyclic Aromatic Hydrocarbon Mixture Toxicity in Hyalella azteca. 1. Response Surfaces and Isoboles To Measure Non-additive Mixture Toxicity and Ecological Risk.

PubMed

Gauthier, Patrick T; Norwood, Warren P; Prepas, Ellie E; Pyle, Greg G

2015-10-06

Mixtures of metals and polycyclic aromatic hydrocarbons (PAHs) occur ubiquitously in aquatic environments, yet relatively little is known regarding their potential to produce non-additive toxicity (i.e., antagonism or potentiation). A review of the lethality of metal-PAH mixtures in aquatic biota revealed that more-than-additive lethality is as common as strictly additive effects. Approaches to ecological risk assessment do not consider non-additive toxicity of metal-PAH mixtures. Forty-eight-hour water-only binary mixture toxicity experiments were conducted to determine the additive toxic nature of mixtures of Cu, Cd, V, or Ni with phenanthrene (PHE) or phenanthrenequinone (PHQ) using the aquatic amphipod Hyalella azteca. In cases where more-than-additive toxicity was observed, we calculated the possible mortality rates at Canada's environmental water quality guideline concentrations. We used a three-dimensional response surface isobole model-based approach to compare the observed co-toxicity in juvenile amphipods to predicted outcomes based on concentration addition or effects addition mixtures models. More-than-additive lethality was observed for all Cu-PHE, Cu-PHQ, and several Cd-PHE, Cd-PHQ, and Ni-PHE mixtures. Our analysis predicts Cu-PHE, Cu-PHQ, Cd-PHE, and Cd-PHQ mixtures at the Canadian Water Quality Guideline concentrations would produce 7.5%, 3.7%, 4.4% and 1.4% mortality, respectively.

The simultaneous mass and energy evaporation (SM2E) model.

PubMed

Choudhary, Rehan; Klauda, Jeffery B

2016-01-01

In this article, the Simultaneous Mass and Energy Evaporation (SM2E) model is presented. The SM2E model is based on theoretical models for mass and energy transfer. The theoretical models systematically under or over predicted at various flow conditions: laminar, transition, and turbulent. These models were harmonized with experimental measurements to eliminate systematic under or over predictions; a total of 113 measured evaporation rates were used. The SM2E model can be used to estimate evaporation rates for pure liquids as well as liquid mixtures at laminar, transition, and turbulent flow conditions. However, due to limited availability of evaporation data, the model has so far only been tested against data for pure liquids and binary mixtures. The model can take evaporative cooling into account and when the temperature of the evaporating liquid or liquid mixture is known (e.g., isothermal evaporation), the SM2E model reduces to a mass transfer-only model.

PACE: Probabilistic Assessment for Contributor Estimation- A machine learning-based assessment of the number of contributors in DNA mixtures.

PubMed

Marciano, Michael A; Adelman, Jonathan D

2017-03-01

The deconvolution of DNA mixtures remains one of the most critical challenges in the field of forensic DNA analysis. In addition, of all the data features required to perform such deconvolution, the number of contributors in the sample is widely considered the most important, and, if incorrectly chosen, the most likely to negatively influence the mixture interpretation of a DNA profile. Unfortunately, most current approaches to mixture deconvolution require the assumption that the number of contributors is known by the analyst, an assumption that can prove to be especially faulty when faced with increasingly complex mixtures of 3 or more contributors. In this study, we propose a probabilistic approach for estimating the number of contributors in a DNA mixture that leverages the strengths of machine learning. To assess this approach, we compare classification performances of six machine learning algorithms and evaluate the model from the top-performing algorithm against the current state of the art in the field of contributor number classification. Overall results show over 98% accuracy in identifying the number of contributors in a DNA mixture of up to 4 contributors. Comparative results showed 3-person mixtures had a classification accuracy improvement of over 6% compared to the current best-in-field methodology, and that 4-person mixtures had a classification accuracy improvement of over 20%. The Probabilistic Assessment for Contributor Estimation (PACE) also accomplishes classification of mixtures of up to 4 contributors in less than 1s using a standard laptop or desktop computer. Considering the high classification accuracy rates, as well as the significant time commitment required by the current state of the art model versus seconds required by a machine learning-derived model, the approach described herein provides a promising means of estimating the number of contributors and, subsequently, will lead to improved DNA mixture interpretation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Benchmarking density functionals for hydrogen-helium mixtures with quantum Monte Carlo: Energetics, pressures, and forces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clay, Raymond C.; Holzmann, Markus; Ceperley, David M.

An accurate understanding of the phase diagram of dense hydrogen and helium mixtures is a crucial component in the construction of accurate models of Jupiter, Saturn, and Jovian extrasolar planets. Though DFT based rst principles methods have the potential to provide the accuracy and computational e ciency required for this task, recent benchmarking in hydrogen has shown that achieving this accuracy requires a judicious choice of functional, and a quanti cation of the errors introduced. In this work, we present a quantum Monte Carlo based benchmarking study of a wide range of density functionals for use in hydrogen-helium mixtures atmore » thermodynamic conditions relevant for Jovian planets. Not only do we continue our program of benchmarking energetics and pressures, but we deploy QMC based force estimators and use them to gain insights into how well the local liquid structure is captured by di erent density functionals. We nd that TPSS, BLYP and vdW-DF are the most accurate functionals by most metrics, and that the enthalpy, energy, and pressure errors are very well behaved as a function of helium concentration. Beyond this, we highlight and analyze the major error trends and relative di erences exhibited by the major classes of functionals, and estimate the magnitudes of these e ects when possible.« less

Benchmarking density functionals for hydrogen-helium mixtures with quantum Monte Carlo: Energetics, pressures, and forces

DOE PAGES

Clay, Raymond C.; Holzmann, Markus; Ceperley, David M.; ...

2016-01-19

An accurate understanding of the phase diagram of dense hydrogen and helium mixtures is a crucial component in the construction of accurate models of Jupiter, Saturn, and Jovian extrasolar planets. Though DFT based rst principles methods have the potential to provide the accuracy and computational e ciency required for this task, recent benchmarking in hydrogen has shown that achieving this accuracy requires a judicious choice of functional, and a quanti cation of the errors introduced. In this work, we present a quantum Monte Carlo based benchmarking study of a wide range of density functionals for use in hydrogen-helium mixtures atmore » thermodynamic conditions relevant for Jovian planets. Not only do we continue our program of benchmarking energetics and pressures, but we deploy QMC based force estimators and use them to gain insights into how well the local liquid structure is captured by di erent density functionals. We nd that TPSS, BLYP and vdW-DF are the most accurate functionals by most metrics, and that the enthalpy, energy, and pressure errors are very well behaved as a function of helium concentration. Beyond this, we highlight and analyze the major error trends and relative di erences exhibited by the major classes of functionals, and estimate the magnitudes of these e ects when possible.« less

Dissociation of iodine molecules and singlet oxygen generation in O2 - I2 mixture induced by 1315-nm laser radiation

NASA Astrophysics Data System (ADS)

Zagidullin, M. V.; Khvatov, N. A.; Malyshev, M. S.; Azyazov, V. N.

2017-11-01

It is observed that laser light at a wavelength of 1315 nm induces continuous stable fluorescence at the O2(b1Σ → X3Σ) and I2(B3Πu → X1Σ) bands in a O2 - I2 mixture preliminarily irradiated at a wavelength of 532 nm to achieve partial photolysis of iodine molecules. This testifies to generation of iodine atoms and excited O2(a1Δ), O2(b1Σ), and I2(B3Πu) molecules in the O2 - I2 mixture under irradiation at 1315 nm.

Finite mixture models for the computation of isotope ratios in mixed isotopic samples

NASA Astrophysics Data System (ADS)

Koffler, Daniel; Laaha, Gregor; Leisch, Friedrich; Kappel, Stefanie; Prohaska, Thomas

2013-04-01

Finite mixture models have been used for more than 100 years, but have seen a real boost in popularity over the last two decades due to the tremendous increase in available computing power. The areas of application of mixture models range from biology and medicine to physics, economics and marketing. These models can be applied to data where observations originate from various groups and where group affiliations are not known, as is the case for multiple isotope ratios present in mixed isotopic samples. Recently, the potential of finite mixture models for the computation of 235U/238U isotope ratios from transient signals measured in individual (sub-)µm-sized particles by laser ablation - multi-collector - inductively coupled plasma mass spectrometry (LA-MC-ICPMS) was demonstrated by Kappel et al. [1]. The particles, which were deposited on the same substrate, were certified with respect to their isotopic compositions. Here, we focus on the statistical model and its application to isotope data in ecogeochemistry. Commonly applied evaluation approaches for mixed isotopic samples are time-consuming and are dependent on the judgement of the analyst. Thus, isotopic compositions may be overlooked due to the presence of more dominant constituents. Evaluation using finite mixture models can be accomplished unsupervised and automatically. The models try to fit several linear models (regression lines) to subgroups of data taking the respective slope as estimation for the isotope ratio. The finite mixture models are parameterised by: • The number of different ratios. • Number of points belonging to each ratio-group. • The ratios (i.e. slopes) of each group. Fitting of the parameters is done by maximising the log-likelihood function using an iterative expectation-maximisation (EM) algorithm. In each iteration step, groups of size smaller than a control parameter are dropped; thereby the number of different ratios is determined. The analyst only influences some control parameters of the algorithm, i.e. the maximum count of ratios, the minimum relative group-size of data points belonging to each ratio has to be defined. Computation of the models can be done with statistical software. In this study Leisch and Grün's flexmix package [2] for the statistical open-source software R was applied. A code example is available in the electronic supplementary material of Kappel et al. [1]. In order to demonstrate the usefulness of finite mixture models in fields dealing with the computation of multiple isotope ratios in mixed samples, a transparent example based on simulated data is presented and problems regarding small group-sizes are illustrated. In addition, the application of finite mixture models to isotope ratio data measured in uranium oxide particles is shown. The results indicate that finite mixture models perform well in computing isotope ratios relative to traditional estimation procedures and can be recommended for more objective and straightforward calculation of isotope ratios in geochemistry than it is current practice. [1] S. Kappel, S. Boulyga, L. Dorta, D. Günther, B. Hattendorf, D. Koffler, G. Laaha, F. Leisch and T. Prohaska: Evaluation Strategies for Isotope Ratio Measurements of Single Particles by LA-MC-ICPMS, Analytical and Bioanalytical Chemistry, 2013, accepted for publication on 2012-12-18 (doi: 10.1007/s00216-012-6674-3) [2] B. Grün and F. Leisch: Fitting finite mixtures of generalized linear regressions in R. Computational Statistics & Data Analysis, 51(11), 5247-5252, 2007. (doi:10.1016/j.csda.2006.08.014)

Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

An analysis of lethal and sublethal interactions among type I and type II pyrethroid pesticide mixtures using standard Hyalella azteca water column toxicity tests.

PubMed

Hoffmann, Krista Callinan; Deanovic, Linda; Werner, Inge; Stillway, Marie; Fong, Stephanie; Teh, Swee

2016-10-01

A novel 2-tiered analytical approach was used to characterize and quantify interactions between type I and type II pyrethroids in Hyalella azteca using standardized water column toxicity tests. Bifenthrin, permethrin, cyfluthrin, and lambda-cyhalothrin were tested in all possible binary combinations across 6 experiments. All mixtures were analyzed for 4-d lethality, and 2 of the 6 mixtures (permethrin-bifenthrin and permethrin-cyfluthrin) were tested for subchronic 10-d lethality and sublethal effects on swimming motility and growth. Mixtures were initially analyzed for interactions using regression analyses, and subsequently compared with the additive models of concentration addition and independent action to further characterize mixture responses. Negative interactions (antagonistic) were significant in 2 of the 6 mixtures tested, including cyfluthrin-bifenthrin and cyfluthrin-permethrin, but only on the acute 4-d lethality endpoint. In both cases mixture responses fell between the additive models of concentration addition and independent action. All other mixtures were additive across 4-d lethality, and bifenthrin-permethrin and cyfluthrin-permethrin were also additive in terms of subchronic 10-d lethality and sublethal responses. Environ Toxicol Chem 2016;35:2542-2549. © 2016 SETAC. © 2016 SETAC.

Heat transfer during condensation of steam from steam-gas mixtures in the passive safety systems of nuclear power plants

NASA Astrophysics Data System (ADS)

Portnova, N. M.; Smirnov, Yu B.

2017-11-01

A theoretical model for calculation of heat transfer during condensation of multicomponent vapor-gas mixtures on vertical surfaces, based on film theory and heat and mass transfer analogy is proposed. Calculations were performed for the conditions implemented in experimental studies of heat transfer during condensation of steam-gas mixtures in the passive safety systems of PWR-type reactors of different designs. Calculated values of heat transfer coefficients for condensation of steam-air, steam-air-helium and steam-air-hydrogen mixtures at pressures of 0.2 to 0.6 MPa and of steam-nitrogen mixture at the pressures of 0.4 to 2.6 MPa were obtained. The composition of mixtures and vapor-to-surface temperature difference were varied within wide limits. Tube length ranged from 0.65 to 9.79m. The condensation of all steam-gas mixtures took place in a laminar-wave flow mode of condensate film and turbulent free convection in the diffusion boundary layer. The heat transfer coefficients obtained by calculation using the proposed model are in good agreement with the considered experimental data for both the binary and ternary mixtures.

Combining measurements to estimate properties and characterization extent of complex biochemical mixtures; applications to Heparan Sulfate

PubMed Central

Pradines, Joël R.; Beccati, Daniela; Lech, Miroslaw; Ozug, Jennifer; Farutin, Victor; Huang, Yongqing; Gunay, Nur Sibel; Capila, Ishan

2016-01-01

Complex mixtures of molecular species, such as glycoproteins and glycosaminoglycans, have important biological and therapeutic functions. Characterization of these mixtures with analytical chemistry measurements is an important step when developing generic drugs such as biosimilars. Recent developments have focused on analytical methods and statistical approaches to test similarity between mixtures. The question of how much uncertainty on mixture composition is reduced by combining several measurements still remains mostly unexplored. Mathematical frameworks to combine measurements, estimate mixture properties, and quantify remaining uncertainty, i.e. a characterization extent, are introduced here. Constrained optimization and mathematical modeling are applied to a set of twenty-three experimental measurements on heparan sulfate, a mixture of linear chains of disaccharides having different levels of sulfation. While this mixture has potentially over two million molecular species, mathematical modeling and the small set of measurements establish the existence of nonhomogeneity of sulfate level along chains and the presence of abundant sulfate repeats. Constrained optimization yields not only estimations of sulfate repeats and sulfate level at each position in the chains but also bounds on these levels, thereby estimating the extent of characterization of the sulfation pattern which is achieved by the set of measurements. PMID:27112127

Combining measurements to estimate properties and characterization extent of complex biochemical mixtures; applications to Heparan Sulfate.

PubMed

Pradines, Joël R; Beccati, Daniela; Lech, Miroslaw; Ozug, Jennifer; Farutin, Victor; Huang, Yongqing; Gunay, Nur Sibel; Capila, Ishan

2016-04-26

Complex mixtures of molecular species, such as glycoproteins and glycosaminoglycans, have important biological and therapeutic functions. Characterization of these mixtures with analytical chemistry measurements is an important step when developing generic drugs such as biosimilars. Recent developments have focused on analytical methods and statistical approaches to test similarity between mixtures. The question of how much uncertainty on mixture composition is reduced by combining several measurements still remains mostly unexplored. Mathematical frameworks to combine measurements, estimate mixture properties, and quantify remaining uncertainty, i.e. a characterization extent, are introduced here. Constrained optimization and mathematical modeling are applied to a set of twenty-three experimental measurements on heparan sulfate, a mixture of linear chains of disaccharides having different levels of sulfation. While this mixture has potentially over two million molecular species, mathematical modeling and the small set of measurements establish the existence of nonhomogeneity of sulfate level along chains and the presence of abundant sulfate repeats. Constrained optimization yields not only estimations of sulfate repeats and sulfate level at each position in the chains but also bounds on these levels, thereby estimating the extent of characterization of the sulfation pattern which is achieved by the set of measurements.

Combining measurements to estimate properties and characterization extent of complex biochemical mixtures; applications to Heparan Sulfate

NASA Astrophysics Data System (ADS)

Pradines, Joël R.; Beccati, Daniela; Lech, Miroslaw; Ozug, Jennifer; Farutin, Victor; Huang, Yongqing; Gunay, Nur Sibel; Capila, Ishan

2016-04-01

Complex mixtures of molecular species, such as glycoproteins and glycosaminoglycans, have important biological and therapeutic functions. Characterization of these mixtures with analytical chemistry measurements is an important step when developing generic drugs such as biosimilars. Recent developments have focused on analytical methods and statistical approaches to test similarity between mixtures. The question of how much uncertainty on mixture composition is reduced by combining several measurements still remains mostly unexplored. Mathematical frameworks to combine measurements, estimate mixture properties, and quantify remaining uncertainty, i.e. a characterization extent, are introduced here. Constrained optimization and mathematical modeling are applied to a set of twenty-three experimental measurements on heparan sulfate, a mixture of linear chains of disaccharides having different levels of sulfation. While this mixture has potentially over two million molecular species, mathematical modeling and the small set of measurements establish the existence of nonhomogeneity of sulfate level along chains and the presence of abundant sulfate repeats. Constrained optimization yields not only estimations of sulfate repeats and sulfate level at each position in the chains but also bounds on these levels, thereby estimating the extent of characterization of the sulfation pattern which is achieved by the set of measurements.

Mammalian Toxicological Evaluation of TNT Wastewaters. Volume II. Acute and Subacute Mammalian Toxicity of TNT and LAP Mixture

DTIC Science & Technology

1979-06-01

different species of fish and four Invertebrate species. 17 Irradiated mixtures (with >50% TNT degradation) were invariably less toxic than the...statistically. Moreover, a marked lymphocytosis was apparent at this level. Some parameters, especially the RBC, Hgb, and/or Hct, were significantly...on treatment after 13 weeks had lymphocytosis , the males that continued on study but were allowed 4 weeks of recovery had a slight granulocytosis

Novel chemometric strategy based on the application of artificial neural networks to crossed mixture design for the improvement of recombinant protein production in continuous culture.

PubMed

Didier, Caroline; Forno, Guillermina; Etcheverrigaray, Marina; Kratje, Ricardo; Goicoechea, Héctor

2009-09-21

The optimal blends of six compounds that should be present in culture media used in recombinant protein production were determined by means of artificial neural networks (ANN) coupled with crossed mixture experimental design. This combination constitutes a novel approach to develop a medium for cultivating genetically engineered mammalian cells. The compounds were collected in two mixtures of three elements each, and the experimental space was determined by a crossed mixture design. Empirical data from 51 experimental units were used in a multiresponse analysis to train artificial neural networks which satisfy different requirements, in order to define two new culture media (Medium 1 and Medium 2) to be used in a continuous biopharmaceutical production process. These media were tested in a bioreactor to produce a recombinant protein in CHO cells. Remarkably, for both predicted media all responses satisfied the predefined goals pursued during the analysis, except in the case of the specific growth rate (mu) observed for Medium 1. ANN analysis proved to be a suitable methodology to be used when dealing with complex experimental designs, as frequently occurs in the optimization of production processes in the biotechnology area. The present work is a new example of the use of ANN for the resolution of a complex, real life system, successfully employed in the context of a biopharmaceutical production process.

Functionally redundant but dissimilar microbial communities within biogas reactors treating maize silage in co-fermentation with sugar beet silage

PubMed Central

Langer, Susanne G; Ahmed, Sharif; Einfalt, Daniel; Bengelsdorf, Frank R; Kazda, Marian

2015-01-01

Numerous observations indicate a high flexibility of microbial communities in different biogas reactors during anaerobic digestion. Here, we describe the functional redundancy and structural changes of involved microbial communities in four lab-scale continuously stirred tank reactors (CSTRs, 39°C, 12 L volume) supplied with different mixtures of maize silage (MS) and sugar beet silage (SBS) over 80 days. Continuously stirred tank reactors were fed with mixtures of MS and SBS in volatile solid ratios of 1:0 (Continuous Fermenter (CF) 1), 6:1 (CF2), 3:1 (CF3), 1:3 (CF4) with equal organic loading rates (OLR 1.25 kgVS m−3 d−1) and showed similar biogas production rates in all reactors. The compositions of bacterial and archaeal communities were analysed by 454 amplicon sequencing approach based on 16S rRNA genes. Both bacterial and archaeal communities shifted with increasing amounts of SBS. Especially pronounced were changes in the archaeal composition towards Methanosarcina with increasing proportion of SBS, while Methanosaeta declined simultaneously. Compositional shifts within the microbial communities did not influence the respective biogas production rates indicating that these communities adapted to environmental conditions induced by different feedstock mixtures. The diverse microbial communities optimized their metabolism in a way that ensured efficient biogas production. PMID:26200922

Nature and prevalence of non-additive toxic effects in industrially relevant mixtures of organic chemicals.

PubMed

Parvez, Shahid; Venkataraman, Chandra; Mukherji, Suparna

2009-06-01

The concentration addition (CA) and the independent action (IA) models are widely used for predicting mixture toxicity based on its composition and individual component dose-response profiles. However, the prediction based on these models may be inaccurate due to interaction among mixture components. In this work, the nature and prevalence of non-additive effects were explored for binary, ternary and quaternary mixtures composed of hydrophobic organic compounds (HOCs). The toxicity of each individual component and mixture was determined using the Vibrio fischeri bioluminescence inhibition assay. For each combination of chemicals specified by the 2(n) factorial design, the percent deviation of the predicted toxic effect from the measured value was used to characterize mixtures as synergistic (positive deviation) and antagonistic (negative deviation). An arbitrary classification scheme was proposed based on the magnitude of deviation (d) as: additive (< or =10%, class-I) and moderately (10< d < or =30 %, class-II), highly (30< d < or =50%, class-III) and very highly (>50%, class-IV) antagonistic/synergistic. Naphthalene, n-butanol, o-xylene, catechol and p-cresol led to synergism in mixtures while 1, 2, 4-trimethylbenzene and 1, 3-dimethylnaphthalene contributed to antagonism. Most of the mixtures depicted additive or antagonistic effect. Synergism was prominent in some of the mixtures, such as, pulp and paper, textile dyes, and a mixture composed of polynuclear aromatic hydrocarbons. The organic chemical industry mixture depicted the highest abundance of antagonism and least synergism. Mixture toxicity was found to depend on partition coefficient, molecular connectivity index and relative concentration of the components.

Gaseous emissions from the combustion of a waste mixture containing a high concentration of N2O.

PubMed

Dong, Changqing; Yang, Yongping; Zhang, Junjiao; Lu, Xuefeng

2009-01-01

This paper is focused on reducing the emissions from the combustion of a waste mixture containing a high concentration of N2O. A rate model and an equilibrium model were used to predict gaseous emissions from the combustion of the mixture. The influences of temperature and methane were considered, and the experimental research was carried out in a tabular reactor and a pilot combustion furnace. The results showed that for the waste mixture, the combustion temperature should be in the range of 950-1100 degrees C and the gas residence time should be 2s or higher to reduce emissions.

Mixtures of charged colloid and neutral polymer: Influence of electrostatic interactions on demixing and interfacial tension

NASA Astrophysics Data System (ADS)

Denton, Alan R.; Schmidt, Matthias

2005-06-01

The equilibrium phase behavior of a binary mixture of charged colloids and neutral, nonadsorbing polymers is studied within free-volume theory. A model mixture of charged hard-sphere macroions and ideal, coarse-grained, effective-sphere polymers is mapped first onto a binary hard-sphere mixture with nonadditive diameters and then onto an effective Asakura-Oosawa model [S. Asakura and F. Oosawa, J. Chem. Phys. 22, 1255 (1954)]. The effective model is defined by a single dimensionless parameter—the ratio of the polymer diameter to the effective colloid diameter. For high salt-to-counterion concentration ratios, a free-volume approximation for the free energy is used to compute the fluid phase diagram, which describes demixing into colloid-rich (liquid) and colloid-poor (vapor) phases. Increasing the range of electrostatic interactions shifts the demixing binodal toward higher polymer concentration, stabilizing the mixture. The enhanced stability is attributed to a weakening of polymer depletion-induced attraction between electrostatically repelling macroions. Comparison with predictions of density-functional theory reveals a corresponding increase in the liquid-vapor interfacial tension. The predicted trends in phase stability are consistent with observed behavior of protein-polysaccharide mixtures in food colloids.

Development of small-size tubular-flow continuous reactors for the analysis of operational stability of enzymes in low-water systems.

PubMed

Pirozzi, D; Halling, P J

2001-01-20

A very small-scale continuous flow reactor has been designed for use with enzymes in organic media, particularly for operational stability studies. It is constructed from fairly inexpensive components, and typically uses 5 mg of catalyst and flow rates of 1 to 5 mL/h, so only small quantities of feedstock need to be handled. The design allows control of the thermodynamic water activity of the feed, and works with temperatures up to at least 80 degrees C. The reactor has been operated with both nonpolar (octane) and polar (4-methyl-pentan-2-one) solvents, and with the more viscous solvent-free reactant mixture. It has been applied to studies of the operational stability of lipases from Chromobacterium viscosum (lyophilized powder or polypropylene-adsorbed) and Rhizomucor miehei (Lipozyme) in different experimental conditions. Transesterification of geraniol and ethylcaproate has been adopted as a model transformation.

Investor structure and the price-volume relationship in a continuous double auction market: An agent-based modeling perspective

NASA Astrophysics Data System (ADS)

Zhang, Wei; Bi, Zhengzheng; Shen, Dehua

2017-02-01

This paper investigates the impact of investor structure on the price-volume relationship by simulating a continuous double auction market. Connected with the underlying mechanisms of the price-volume relationship, i.e., the Mixture of Distribution Hypothesis (MDH) and the Sequential Information Arrival Hypothesis (SIAH), the simulation results show that: (1) there exists a strong lead-lag relationship between the return volatility and trading volume when the number of informed investors is close to the number of uninformed investors in the market; (2) as more and more informed investors entering the market, the lead-lag relationship becomes weaker and weaker, while the contemporaneous relationship between the return volatility and trading volume becomes more prominent; (3) when the informed investors are in absolute majority, the market can achieve the new equilibrium immediately. Therefore, we can conclude that the investor structure is a key factor in affecting the price-volume relationship.

Assessment of combined antiandrogenic effects of binary parabens mixtures in a yeast-based reporter assay.

PubMed

Ma, Dehua; Chen, Lujun; Zhu, Xiaobiao; Li, Feifei; Liu, Cong; Liu, Rui

2014-05-01

To date, toxicological studies of endocrine disrupting chemicals (EDCs) have typically focused on single chemical exposures and associated effects. However, exposure to EDCs mixtures in the environment is common. Antiandrogens represent a group of EDCs, which draw increasing attention due to their resultant demasculinization and sexual disruption of aquatic organisms. Although there are a number of in vivo and in vitro studies investigating the combined effects of antiandrogen mixtures, these studies are mainly on selected model compounds such as flutamide, procymidone, and vinclozolin. The aim of the present study is to investigate the combined antiandrogenic effects of parabens, which are widely used antiandrogens in industrial and domestic commodities. A yeast-based human androgen receptor (hAR) assay (YAS) was applied to assess the antiandrogenic activities of n-propylparaben (nPrP), iso-propylparaben (iPrP), methylparaben (MeP), and 4-n-pentylphenol (PeP), as well as the binary mixtures of nPrP with each of the other three antiandrogens. All of the four compounds could exhibit antiandrogenic activity via the hAR. A linear interaction model was applied to quantitatively analyze the interaction between nPrP and each of the other three antiandrogens. The isoboles method was modified to show the variation of combined effects as the concentrations of mixed antiandrogens were changed. Graphs were constructed to show isoeffective curves of three binary mixtures based on the fitted linear interaction model and to evaluate the interaction of the mixed antiandrogens (synergism or antagonism). The combined effect of equimolar combinations of the three mixtures was also considered with the nonlinear isoboles method. The main effect parameters and interaction effect parameters in the linear interaction models of the three mixtures were different from zero. The results showed that any two antiandrogens in their binary mixtures tended to exert equal antiandrogenic activity in the linear concentration ranges. The antiandrogenicity of the binary mixture and the concentration of nPrP were fitted to a sigmoidal model if the concentrations of the other antiandrogens (iPrP, MeP, and PeP) in the mixture were lower than the AR saturation concentrations. Some concave isoboles above the additivity line appeared in all the three mixtures. There were some synergistic effects of the binary mixture of nPrP and MeP at low concentrations in the linear concentration ranges. Interesting, when the antiandrogens concentrations approached the saturation, the interaction between chemicals were antagonistic for all the three mixtures tested. When the toxicity of the three mixtures was assessed using nonlinear isoboles, only antagonism was observed for equimolar combinations of nPrP and iPrP as the concentrations were increased from the no-observed-effect-concentration (NOEC) to effective concentration of 80%. In addition, the interactions were changed from synergistic to antagonistic as effective concentrations were increased in the equimolar combinations of nPrP and MeP, as well as nPrP and PeP. The combined effects of three binary antiandrogens mixtures in the linear ranges were successfully evaluated by curve fitting and isoboles. The combined effects of specific binary mixtures varied depending on the concentrations of the chemicals in the mixtures. At low concentrations in the linear concentration ranges, there was synergistic interaction existing in the binary mixture of nPrP and MeP. The interaction tended to be antagonistic as the antiandrogens approached saturation concentrations in mixtures of nPrP with each of the other three antiandrogens. The synergistic interaction was also found in the equimolar combinations of nPrP and MeP, as well as nPrP and PeP, at low concentrations with another method of nonlinear isoboles. The mixture activities of binary antiandrogens had a tendency towards antagonism at high concentrations and synergism at low concentrations.

Mixture models in diagnostic meta-analyses--clustering summary receiver operating characteristic curves accounted for heterogeneity and correlation.

PubMed

Schlattmann, Peter; Verba, Maryna; Dewey, Marc; Walther, Mario

2015-01-01

Bivariate linear and generalized linear random effects are frequently used to perform a diagnostic meta-analysis. The objective of this article was to apply a finite mixture model of bivariate normal distributions that can be used for the construction of componentwise summary receiver operating characteristic (sROC) curves. Bivariate linear random effects and a bivariate finite mixture model are used. The latter model is developed as an extension of a univariate finite mixture model. Two examples, computed tomography (CT) angiography for ruling out coronary artery disease and procalcitonin as a diagnostic marker for sepsis, are used to estimate mean sensitivity and mean specificity and to construct sROC curves. The suggested approach of a bivariate finite mixture model identifies two latent classes of diagnostic accuracy for the CT angiography example. Both classes show high sensitivity but mainly two different levels of specificity. For the procalcitonin example, this approach identifies three latent classes of diagnostic accuracy. Here, sensitivities and specificities are quite different as such that sensitivity increases with decreasing specificity. Additionally, the model is used to construct componentwise sROC curves and to classify individual studies. The proposed method offers an alternative approach to model between-study heterogeneity in a diagnostic meta-analysis. Furthermore, it is possible to construct sROC curves even if a positive correlation between sensitivity and specificity is present. Copyright © 2015 Elsevier Inc. All rights reserved.

Modeling Grade IV Gas Emboli using a Limited Failure Population Model with Random Effects

NASA Technical Reports Server (NTRS)

Thompson, Laura A.; Conkin, Johnny; Chhikara, Raj S.; Powell, Michael R.

2002-01-01

Venous gas emboli (VGE) (gas bubbles in venous blood) are associated with an increased risk of decompression sickness (DCS) in hypobaric environments. A high grade of VGE can be a precursor to serious DCS. In this paper, we model time to Grade IV VGE considering a subset of individuals assumed to be immune from experiencing VGE. Our data contain monitoring test results from subjects undergoing up to 13 denitrogenation test procedures prior to exposure to a hypobaric environment. The onset time of Grade IV VGE is recorded as contained within certain time intervals. We fit a parametric (lognormal) mixture survival model to the interval-and right-censored data to account for the possibility of a subset of "cured" individuals who are immune to the event. Our model contains random subject effects to account for correlations between repeated measurements on a single individual. Model assessments and cross-validation indicate that this limited failure population mixture model is an improvement over a model that does not account for the potential of a fraction of cured individuals. We also evaluated some alternative mixture models. Predictions from the best fitted mixture model indicate that the actual process is reasonably approximated by a limited failure population model.

A globally accurate theory for a class of binary mixture models

NASA Astrophysics Data System (ADS)

Dickman, Adriana G.; Stell, G.

The self-consistent Ornstein-Zernike approximation results for the 3D Ising model are used to obtain phase diagrams for binary mixtures described by decorated models, yielding the plait point, binodals, and closed-loop coexistence curves for the models proposed by Widom, Clark, Neece, and Wheeler. The results are in good agreement with series expansions and experiments.

Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts

USGS Publications Warehouse

Dorazio, Robert M.; Martin, Juulien; Edwards, Holly H.

2013-01-01

The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts.

PubMed

Dorazio, Robert M; Martin, Julien; Edwards, Holly H

2013-07-01

The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

Bayesian Finite Mixtures for Nonlinear Modeling of Educational Data.

ERIC Educational Resources Information Center

Tirri, Henry; And Others

A Bayesian approach for finding latent classes in data is discussed. The approach uses finite mixture models to describe the underlying structure in the data and demonstrate that the possibility of using full joint probability models raises interesting new prospects for exploratory data analysis. The concepts and methods discussed are illustrated…

Kinetic model for the vibrational energy exchange in flowing molecular gas mixtures. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Offenhaeuser, F.

1987-01-01

The present study is concerned with the development of a computational model for the description of the vibrational energy exchange in flowing gas mixtures, taking into account a given number of energy levels for each vibrational degree of freedom. It is possible to select an arbitrary number of energy levels. The presented model uses values in the range from 10 to approximately 40. The distribution of energy with respect to these levels can differ from the equilibrium distribution. The kinetic model developed can be employed for arbitrary gaseous mixtures with an arbitrary number of vibrational degrees of freedom for each type of gas. The application of the model to CO2-H2ON2-O2-He mixtures is discussed. The obtained relations can be utilized in a study of the suitability of radiation-related transitional processes, involving the CO2 molecule, for laser applications. It is found that the computational results provided by the model agree very well with experimental data obtained for a CO2 laser. Possibilities for the activation of a 16-micron and 14-micron laser are considered.

Program on the combustion chemistry of low- and intermediate-Btu gas mixtures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1981-11-30

Low and intermediate Btu (LBTU and IBTU) gas mixtures are essentially mixtures of CO, H/sub 2/ and CH/sub 4/ diluted with nitrogen and CO/sub 2/. Although the combustion properties of these three fuels have been extensively investigated and their individual combustion kinetics are reasonably well established, prediction techniques for applying these gas mixtures remain for the most part empirical. This program has aimed to bring together and apply some of the fundamental combustion parameters to the CO-H/sub 2/-CH/sub 4/ flame system with the hope of reducing some of this empiricism. Four topical reports have resulted from this program. This finalmore » report summarizes these reports and other activities undertaken in this program. This program was initiated June 22, 1976 under ERDA Contract No. E(49-18)-2406 and was later continued under DOE/PETC and DOE Contract No. DE-AC22-76ET10653.« less

Rapid gas hydrate formation process

DOEpatents

Brown, Thomas D.; Taylor, Charles E.; Unione, Alfred J.

2013-01-15

The disclosure provides a method and apparatus for forming gas hydrates from a two-phase mixture of water and a hydrate forming gas. The two-phase mixture is created in a mixing zone which may be wholly included within the body of a spray nozzle. The two-phase mixture is subsequently sprayed into a reaction zone, where the reaction zone is under pressure and temperature conditions suitable for formation of the gas hydrate. The reaction zone pressure is less than the mixing zone pressure so that expansion of the hydrate-forming gas in the mixture provides a degree of cooling by the Joule-Thompson effect and provides more intimate mixing between the water and the hydrate-forming gas. The result of the process is the formation of gas hydrates continuously and with a greatly reduced induction time. An apparatus for conduct of the method is further provided.

Physical properties of new binary antiferroelectric liquid crystal mixtures

NASA Astrophysics Data System (ADS)

Fitas, Jakub; Jaworska-Gołąb, Teresa; Deptuch, Aleksandra; Tykarska, Marzena; Kurp, Katarzyna; Żurowska, Magdalena; Marzec, Monika

2018-02-01

Three newly prepared binary mixtures exhibiting chiral tilted smectic phases have been studied using differential scanning calorimetry, dielectric spectroscopy and electro-optic method, as well as X-ray diffraction. Broad temperature range of ferroelectric and antiferroelectric phases was detected in these mixtures and temperature dependence of spontaneous polarization, tilt angle and switching time were measured for all of them. It's occurred that all of the studied mixtures are orthoconic antiferroelectric liquid crystals. Based on the X-ray diffraction results, the temperature dependence of layer thickness in the paraelectric, ferroelectric and antiferroelectric phases was found. By using dielectric spectroscopy, Goldstone mode was identified in the ferroelectric phase, while antiphase fluctuations of azimuthal angle have been found in the antiferroelectric phase. Based on the results of the complementary methods, the transition temperatures were found as well as the order of the para-ferroelectric phase transition was determined as non-continuous one with critical parameter β equal to ca. 0.25.

MODEL OF ADDITIVE EFFECTS OF MIXTURES OF NARCOTIC CHEMICALS

EPA Science Inventory

Biological effects data with single chemicals are far more abundant than with mixtures. et, environmental exposures to chemical mixtures, for example near hazardous waste sites or nonpoint sources, are very common and using test data from single chemicals to approximate effects o...

Thermodynamic properties of model CdTe/CdSe mixtures

DOE PAGES

van Swol, Frank; Zhou, Xiaowang W.; Challa, Sivakumar R.; ...

2015-02-20

We report on the thermodynamic properties of binary compound mixtures of model groups II–VI semiconductors. We use the recently introduced Stillinger–Weber Hamiltonian to model binary mixtures of CdTe and CdSe. We use molecular dynamics simulations to calculate the volume and enthalpy of mixing as a function of mole fraction. The lattice parameter of the mixture closely follows Vegard's law: a linear relation. This implies that the excess volume is a cubic function of mole fraction. A connection is made with hard sphere models of mixed fcc and zincblende structures. We found that the potential energy exhibits a positive deviation frommore » ideal soluton behaviour; the excess enthalpy is nearly independent of temperatures studied (300 and 533 K) and is well described by a simple cubic function of the mole fraction. Using a regular solution approach (combining non-ideal behaviour for the enthalpy with ideal solution behaviour for the entropy of mixing), we arrive at the Gibbs free energy of the mixture. The Gibbs free energy results indicate that the CdTe and CdSe mixtures exhibit phase separation. The upper consolute temperature is found to be 335 K. Finally, we provide the surface energy as a function of composition. Moreover, it roughly follows ideal solution theory, but with a negative deviation (negative excess surface energy). This indicates that alloying increases the stability, even for nano-particles.« less

Second law of thermodynamics in volume diffusion hydrodynamics in multicomponent gas mixtures

NASA Astrophysics Data System (ADS)

Dadzie, S. Kokou

2012-10-01

We presented the thermodynamic structure of a new continuum flow model for multicomponent gas mixtures. The continuum model is based on a volume diffusion concept involving specific species. It is independent of the observer's reference frame and enables a straightforward tracking of a selected species within a mixture composed of a large number of constituents. A method to derive the second law and constitutive equations accompanying the model is presented. Using the configuration of a rotating fluid we illustrated an example of non-classical flow physics predicted by new contributions in the entropy and constitutive equations.

Estimation of performance of a J-T refrigerators operating with nitrogen-hydrocarbon mixtures and a coiled tubes-in-tube heat exchanger

NASA Astrophysics Data System (ADS)

Satya Meher, R.; Venkatarathnam, G.

2018-06-01

The exergy efficiency of Joule-Thomson (J-T) refrigerators operating with mixtures (MRC systems) strongly depends on the choice of refrigerant mixture and the performance of the heat exchanger used. Helically coiled, multiple tubes-in-tube heat exchangers with an effectiveness of over 96% are widely used in these types of systems. All the current studies focus only on the different heat transfer correlations and the uncertainty in predicting performance of the heat exchanger alone. The main focus of this work is to estimate the uncertainty in cooling capacity when the homogenous model is used by comparing the theoretical and experimental studies. The comparisons have been extended to some two-phase models present in the literature as well. Experiments have been carried out on a J-T refrigerator at a fixed heat load of 10 W with different nitrogen-hydrocarbon mixtures in the evaporator temperature range of 100-120 K. Different heat transfer models have been used to predict the temperature profiles as well as the cooling capacity of the refrigerator. The results show that the homogenous two-phase flow model is probably the most suitable model for rating the cooling capacity of a J-T refrigerator operating with nitrogen-hydrocarbon mixtures.

Interactions and Toxicity of Cu-Zn mixtures to Hordeum vulgare in Different Soils Can Be Rationalized with Bioavailability-Based Prediction Models.

PubMed

Qiu, Hao; Versieren, Liske; Rangel, Georgina Guzman; Smolders, Erik

2016-01-19

Soil contamination with copper (Cu) is often associated with zinc (Zn), and the biological response to such mixed contamination is complex. Here, we investigated Cu and Zn mixture toxicity to Hordeum vulgare in three different soils, the premise being that the observed interactions are mainly due to effects on bioavailability. The toxic effect of Cu and Zn mixtures on seedling root elongation was more than additive (i.e., synergism) in soils with high and medium cation-exchange capacity (CEC) but less than additive (antagonism) in a low-CEC soil. This was found when we expressed the dose as the conventional total soil concentration. In contrast, antagonism was found in all soils when we expressed the dose as free-ion activities in soil solution, indicating that there is metal-ion competition for binding to the plant roots. Neither a concentration addition nor an independent action model explained mixture effects, irrespective of the dose expressions. In contrast, a multimetal BLM model and a WHAM-Ftox model successfully explained the mixture effects across all soils and showed that bioavailability factors mainly explain the interactions in soils. The WHAM-Ftox model is a promising tool for the risk assessment of mixed-metal contamination in soils.

Estimating Lion Abundance using N-mixture Models for Social Species

PubMed Central

Belant, Jerrold L.; Bled, Florent; Wilton, Clay M.; Fyumagwa, Robert; Mwampeta, Stanslaus B.; Beyer, Dean E.

2016-01-01

Declining populations of large carnivores worldwide, and the complexities of managing human-carnivore conflicts, require accurate population estimates of large carnivores to promote their long-term persistence through well-informed management We used N-mixture models to estimate lion (Panthera leo) abundance from call-in and track surveys in southeastern Serengeti National Park, Tanzania. Because of potential habituation to broadcasted calls and social behavior, we developed a hierarchical observation process within the N-mixture model conditioning lion detectability on their group response to call-ins and individual detection probabilities. We estimated 270 lions (95% credible interval = 170–551) using call-ins but were unable to estimate lion abundance from track data. We found a weak negative relationship between predicted track density and predicted lion abundance from the call-in surveys. Luminosity was negatively correlated with individual detection probability during call-in surveys. Lion abundance and track density were influenced by landcover, but direction of the corresponding effects were undetermined. N-mixture models allowed us to incorporate multiple parameters (e.g., landcover, luminosity, observer effect) influencing lion abundance and probability of detection directly into abundance estimates. We suggest that N-mixture models employing a hierarchical observation process can be used to estimate abundance of other social, herding, and grouping species. PMID:27786283

Estimating Lion Abundance using N-mixture Models for Social Species.

PubMed

Belant, Jerrold L; Bled, Florent; Wilton, Clay M; Fyumagwa, Robert; Mwampeta, Stanslaus B; Beyer, Dean E

2016-10-27

Declining populations of large carnivores worldwide, and the complexities of managing human-carnivore conflicts, require accurate population estimates of large carnivores to promote their long-term persistence through well-informed management We used N-mixture models to estimate lion (Panthera leo) abundance from call-in and track surveys in southeastern Serengeti National Park, Tanzania. Because of potential habituation to broadcasted calls and social behavior, we developed a hierarchical observation process within the N-mixture model conditioning lion detectability on their group response to call-ins and individual detection probabilities. We estimated 270 lions (95% credible interval = 170-551) using call-ins but were unable to estimate lion abundance from track data. We found a weak negative relationship between predicted track density and predicted lion abundance from the call-in surveys. Luminosity was negatively correlated with individual detection probability during call-in surveys. Lion abundance and track density were influenced by landcover, but direction of the corresponding effects were undetermined. N-mixture models allowed us to incorporate multiple parameters (e.g., landcover, luminosity, observer effect) influencing lion abundance and probability of detection directly into abundance estimates. We suggest that N-mixture models employing a hierarchical observation process can be used to estimate abundance of other social, herding, and grouping species.

A comparison of direct and indirect methods for the estimation of health utilities from clinical outcomes.

PubMed

Hernández Alava, Mónica; Wailoo, Allan; Wolfe, Fred; Michaud, Kaleb

2014-10-01

Analysts frequently estimate health state utility values from other outcomes. Utility values like EQ-5D have characteristics that make standard statistical methods inappropriate. We have developed a bespoke, mixture model approach to directly estimate EQ-5D. An indirect method, "response mapping," first estimates the level on each of the 5 dimensions of the EQ-5D and then calculates the expected tariff score. These methods have never previously been compared. We use a large observational database from patients with rheumatoid arthritis (N = 100,398). Direct estimation of UK EQ-5D scores as a function of the Health Assessment Questionnaire (HAQ), pain, and age was performed with a limited dependent variable mixture model. Indirect modeling was undertaken with a set of generalized ordered probit models with expected tariff scores calculated mathematically. Linear regression was reported for comparison purposes. Impact on cost-effectiveness was demonstrated with an existing model. The linear model fits poorly, particularly at the extremes of the distribution. The bespoke mixture model and the indirect approaches improve fit over the entire range of EQ-5D. Mean average error is 10% and 5% lower compared with the linear model, respectively. Root mean squared error is 3% and 2% lower. The mixture model demonstrates superior performance to the indirect method across almost the entire range of pain and HAQ. These lead to differences in cost-effectiveness of up to 20%. There are limited data from patients in the most severe HAQ health states. Modeling of EQ-5D from clinical measures is best performed directly using the bespoke mixture model. This substantially outperforms the indirect method in this example. Linear models are inappropriate, suffer from systematic bias, and generate values outside the feasible range. © The Author(s) 2013.

Simulation of mixture microstructures via particle packing models and their direct comparison with real mixtures

NASA Astrophysics Data System (ADS)

Gulliver, Eric A.

The objective of this thesis to identify and develop techniques providing direct comparison between simulated and real packed particle mixture microstructures containing submicron-sized particles. This entailed devising techniques for simulating powder mixtures, producing real mixtures with known powder characteristics, sectioning real mixtures, interrogating mixture cross-sections, evaluating and quantifying the mixture interrogation process and for comparing interrogation results between mixtures. A drop and roll-type particle-packing model was used to generate simulations of random mixtures. The simulated mixtures were then evaluated to establish that they were not segregated and free from gross defects. A powder processing protocol was established to provide real mixtures for direct comparison and for use in evaluating the simulation. The powder processing protocol was designed to minimize differences between measured particle size distributions and the particle size distributions in the mixture. A sectioning technique was developed that was capable of producing distortion free cross-sections of fine scale particulate mixtures. Tessellation analysis was used to interrogate mixture cross sections and statistical quality control charts were used to evaluate different types of tessellation analysis and to establish the importance of differences between simulated and real mixtures. The particle-packing program generated crescent shaped pores below large particles but realistic looking mixture microstructures otherwise. Focused ion beam milling was the only technique capable of sectioning particle compacts in a manner suitable for stereological analysis. Johnson-Mehl and Voronoi tessellation of the same cross-sections produced tessellation tiles with different the-area populations. Control charts analysis showed Johnson-Mehl tessellation measurements are superior to Voronoi tessellation measurements for detecting variations in mixture microstructure, such as altered particle-size distributions or mixture composition. Control charts based on tessellation measurements were used for direct, quantitative comparisons between real and simulated mixtures. Four sets of simulated and real mixtures were examined. Data from real mixture was matched with simulated data when the samples were well mixed and the particle size distributions and volume fractions of the components were identical. Analysis of mixture components that occupied less than approximately 10 vol% of the mixture was not practical unless the particle size of the component was extremely small and excellent quality high-resolution compositional micrographs of the real sample are available. These methods of analysis should allow future researchers to systematically evaluate and predict the impact and importance of variables such as component volume fraction and component particle size distribution as they pertain to the uniformity of powder mixture microstructures.

Phase-field-based lattice Boltzmann model for incompressible binary fluid systems with density and viscosity contrasts.

PubMed

Zu, Y Q; He, S

2013-04-01

A lattice Boltzmann model (LBM) is proposed based on the phase-field theory to simulate incompressible binary fluids with density and viscosity contrasts. Unlike many existing diffuse interface models which are limited to density matched binary fluids, the proposed model is capable of dealing with binary fluids with moderate density ratios. A new strategy for projecting the phase field to the viscosity field is proposed on the basis of the continuity of viscosity flux. The new LBM utilizes two lattice Boltzmann equations (LBEs): one for the interface tracking and the other for solving the hydrodynamic properties. The LBE for interface tracking can recover the Chan-Hilliard equation without any additional terms; while the LBE for hydrodynamic properties can recover the exact form of the divergence-free incompressible Navier-Stokes equations avoiding spurious interfacial forces. A series of 2D and 3D benchmark tests have been conducted for validation, which include a rigid-body rotation, stationary and moving droplets, a spinodal decomposition, a buoyancy-driven bubbly flow, a layered Poiseuille flow, and the Rayleigh-Taylor instability. It is shown that the proposed method can track the interface with high accuracy and stability and can significantly and systematically reduce the parasitic current across the interface. Comparisons with momentum-based models indicate that the newly proposed velocity-based model can better satisfy the incompressible condition in the flow fields, and eliminate or reduce the velocity fluctuations in the higher-pressure-gradient region and, therefore, achieve a better numerical stability. In addition, the test of a layered Poiseuille flow demonstrates that the proposed scheme for mixture viscosity performs significantly better than the traditional mixture viscosity methods.

Continuously phase-modulated standing surface acoustic waves for separation of particles and cells in microfluidic channels containing multiple pressure nodes

NASA Astrophysics Data System (ADS)

Lee, Junseok; Rhyou, Chanryeol; Kang, Byungjun; Lee, Hyungsuk

2017-04-01

This paper describes continuously phase-modulated standing surface acoustic waves (CPM-SSAW) and its application for particle separation in multiple pressure nodes. A linear change of phase in CPM-SSAW applies a force to particles whose magnitude depends on their size and contrast factors. During continuous phase modulation, we demonstrate that particles with a target dimension are translated in the direction of moving pressure nodes, whereas smaller particles show oscillatory movements. The rate of phase modulation is optimized for separation of target particles from the relationship between mean particle velocity and period of oscillation. The developed technique is applied to separate particles of a target dimension from the particle mixture. Furthermore, we also demonstrate human keratinocyte cells can be separated in the cell and bead mixture. The separation technique is incorporated with a microfluidic channel spanning multiple pressure nodes, which is advantageous over separation in a single pressure node in terms of throughput.

A framework for the use of single-chemical transcriptomics data in predicting the hazards associated with complex mixtures of polycyclic aromatic hydrocarbons.

PubMed

Labib, Sarah; Williams, Andrew; Kuo, Byron; Yauk, Carole L; White, Paul A; Halappanavar, Sabina

2017-07-01

The assumption of additivity applied in the risk assessment of environmental mixtures containing carcinogenic polycyclic aromatic hydrocarbons (PAHs) was investigated using transcriptomics. MutaTMMouse were gavaged for 28 days with three doses of eight individual PAHs, two defined mixtures of PAHs, or coal tar, an environmentally ubiquitous complex mixture of PAHs. Microarrays were used to identify differentially expressed genes (DEGs) in lung tissue collected 3 days post-exposure. Cancer-related pathways perturbed by the individual or mixtures of PAHs were identified, and dose-response modeling of the DEGs was conducted to calculate gene/pathway benchmark doses (BMDs). Individual PAH-induced pathway perturbations (the median gene expression changes for all genes in a pathway relative to controls) and pathway BMDs were applied to models of additivity [i.e., concentration addition (CA), generalized concentration addition (GCA), and independent action (IA)] to generate predicted pathway-specific dose-response curves for each PAH mixture. The predicted and observed pathway dose-response curves were compared to assess the sensitivity of different additivity models. Transcriptomics-based additivity calculation showed that IA accurately predicted the pathway perturbations induced by all mixtures of PAHs. CA did not support the additivity assumption for the defined mixtures; however, GCA improved the CA predictions. Moreover, pathway BMDs derived for coal tar were comparable to BMDs derived from previously published coal tar-induced mouse lung tumor incidence data. These results suggest that in the absence of tumor incidence data, individual chemical-induced transcriptomics changes associated with cancer can be used to investigate the assumption of additivity and to predict the carcinogenic potential of a mixture.

Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches

USGS Publications Warehouse

Duarte, Adam; Adams, Michael J.; Peterson, James T.

2018-01-01

Monitoring animal populations is central to wildlife and fisheries management, and the use of N-mixture models toward these efforts has markedly increased in recent years. Nevertheless, relatively little work has evaluated estimator performance when basic assumptions are violated. Moreover, diagnostics to identify when bias in parameter estimates from N-mixture models is likely is largely unexplored. We simulated count data sets using 837 combinations of detection probability, number of sample units, number of survey occasions, and type and extent of heterogeneity in abundance or detectability. We fit Poisson N-mixture models to these data, quantified the bias associated with each combination, and evaluated if the parametric bootstrap goodness-of-fit (GOF) test can be used to indicate bias in parameter estimates. We also explored if assumption violations can be diagnosed prior to fitting N-mixture models. In doing so, we propose a new model diagnostic, which we term the quasi-coefficient of variation (QCV). N-mixture models performed well when assumptions were met and detection probabilities were moderate (i.e., ≥0.3), and the performance of the estimator improved with increasing survey occasions and sample units. However, the magnitude of bias in estimated mean abundance with even slight amounts of unmodeled heterogeneity was substantial. The parametric bootstrap GOF test did not perform well as a diagnostic for bias in parameter estimates when detectability and sample sizes were low. The results indicate the QCV is useful to diagnose potential bias and that potential bias associated with unidirectional trends in abundance or detectability can be diagnosed using Poisson regression. This study represents the most thorough assessment to date of assumption violations and diagnostics when fitting N-mixture models using the most commonly implemented error distribution. Unbiased estimates of population state variables are needed to properly inform management decision making. Therefore, we also discuss alternative approaches to yield unbiased estimates of population state variables using similar data types, and we stress that there is no substitute for an effective sample design that is grounded upon well-defined management objectives.